{
 "cells": [
  {
   "cell_type": "markdown",
   "source": [
    "# Data Visualisation Guide\n"
   ],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "## Introduction\n",
    "\n",
    "In this chapter, we'll examine the tricks and techniques that will make your data visualisations sing.\n",
    "\n",
    "First, let's import the packages we'll need."
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import plotly.express as px\n",
    "from plotnine import (\n",
    "    options,\n",
    "    geom_tile,\n",
    "    scale_size,\n",
    "    scale_x_continuous,\n",
    "    scale_y_continuous,\n",
    "    ggplot,\n",
    "    geom_point,\n",
    "    aes,\n",
    "    ggtitle\n",
    ")\n",
    "from plotnine.scales import scale_fill_brewer\n",
    "\n",
    "# Set seed for reproducibility\n",
    "np.random.seed(10)\n",
    "# Set max rows displayed for readability\n",
    "pd.set_option(\"display.max_rows\", 6)\n",
    "# Plot settings\n",
    "plt.style.use(\n",
    "    \"https://github.com/aeturrell/coding-for-economists/raw/main/plot_style.txt\"\n",
    ")"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "## The Different Types of Visualisation\n",
    "\n",
    "It's useful to think about three different kinds, or levels, of visualisation:\n",
    "\n",
    "- exploratory\n",
    "\n",
    "- scientific\n",
    "\n",
    "- narrative\n",
    "\n",
    "The first, exploratory visualisation, is the kind that you do when you're looking and data and trying to understand it. Just plotting the data is a really good strategy for getting a feel for any issues there might be. This is perhaps most famously demonstrated by *Anscombe's quartet*: four different datasets with the same mean, standard deviation, and correlation but *very* different data distributions."
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "source": [
    "#TODO hide input\n",
    "x = [10, 8, 13, 9, 11, 14, 6, 4, 12, 7, 5]\n",
    "y1 = [8.04, 6.95, 7.58, 8.81, 8.33, 9.96, 7.24, 4.26, 10.84, 4.82, 5.68]\n",
    "y2 = [9.14, 8.14, 8.74, 8.77, 9.26, 8.10, 6.13, 3.10, 9.13, 7.26, 4.74]\n",
    "y3 = [7.46, 6.77, 12.74, 7.11, 7.81, 8.84, 6.08, 5.39, 8.15, 6.42, 5.73]\n",
    "x4 = [8, 8, 8, 8, 8, 8, 8, 19, 8, 8, 8]\n",
    "y4 = [6.58, 5.76, 7.71, 8.84, 8.47, 7.04, 5.25, 12.50, 5.56, 7.91, 6.89]\n",
    "\n",
    "datasets = {\n",
    "    'I': (x, y1),\n",
    "    'II': (x, y2),\n",
    "    'III': (x, y3),\n",
    "    'IV': (x4, y4)\n",
    "}\n",
    "\n",
    "fig, axs = plt.subplots(2, 2, sharex=True, sharey=True, figsize=(4, 4),\n",
    "                        gridspec_kw={'wspace': 0.08, 'hspace': 0.08})\n",
    "axs[0, 0].set(xlim=(0, 20), ylim=(2, 14))\n",
    "axs[0, 0].set(xticks=(0, 10, 20), yticks=(4, 8, 12))\n",
    "\n",
    "for ax, (label, (x, y)) in zip(axs.flat, datasets.items()):\n",
    "    ax.text(0.1, 0.9, label, fontsize=20, transform=ax.transAxes, va='top')\n",
    "    ax.tick_params(direction='in', top=True, right=True)\n",
    "    ax.plot(x, y, 'o')\n",
    "\n",
    "    # linear regression\n",
    "    p1, p0 = np.polyfit(x, y, deg=1)  # slope, intercept\n",
    "    ax.axline(xy1=(0, p0), slope=p1, color='r', lw=2)\n",
    "\n",
    "    # add text box for the statistics\n",
    "    stats = (f'$\\\\mu$ = {np.mean(y):.2f}\\n'\n",
    "             f'$\\\\sigma$ = {np.std(y):.2f}\\n'\n",
    "             f'$r$ = {np.corrcoef(x, y)[0][1]:.2f}')\n",
    "    bbox = dict(boxstyle='round', fc='blanchedalmond', ec='orange', alpha=0.5)\n",
    "    ax.text(0.95, 0.07, stats, fontsize=9, bbox=bbox,\n",
    "            transform=ax.transAxes, horizontalalignment='right')\n",
    "\n",
    "plt.suptitle(\"Anscombe's Quartet\")\n",
    "plt.show()"
   ],
   "outputs": [
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jfIGdBe4VuByrgNon7Do+PuhbSOEvJwa98RpbYbZiMVtMJ8wW01OoDzPHuh69gLdLcL4jqKJsdhFoa3d4qivO751ms8XkaYpssdhqxKxFpTofAIaZLSZvzckoLcffifs9PcigN75SihErEeTkP77iGo76cCmq0Fc+s8V0AFUcyy6Ki7UpyoxBb7zXoDc+5qY/K1AjNN/YNulwri2x2eHf9xv0xiLvxgx64+OomiV2iY7NBr2xbhHH1+biY5gMwFuTbX3CFkTWsH25z2wxJdv+vY2LIwVVgXgPzlUL9ftysKh9bftrqo6aLab9ZovpftSHmv2x2kMl/NCa4vL1wBKcA7S1ZN4r4Xmg6CyaJ7g4Svet2WI6X4rX8ratDv9+0qA3NipwTxuD3vgM0N61YJyoOCToqIAMav2POFStAdcCXkVxvct8wqA3uqYPloXb3W20vQk/zMURGMc3PseskSqoComu9RTyGfTG/qiS7Y6PkaYD9jf6ULSr77pyvHv+zLXuSRDo5vDv/OqmZovpFM6PtEYZ1HLkbtlGQlYCO80W03YPX9tg0Bs1dSZsr/8VqkorXCzbXiy2RxKOqd5DbeXAPWarMeH4O7AB50DcznFE0LVwmKNCg1icf+8LGuFwHJkqbSqwnePE7ILmMjmOHEUBCwyFLJNgm5MyGW2BME9eS5QTEnRUTA+j0l//V0jBLLfMalEpxxGEhhQwtOpSWKownkxCu8lQwBLitjoYGbYv9zts38TFao2gJv+ZDXrjfQaHtUVs61O8j1prZqTj8LUtY8LxTfJFQ+FrnNhrWRxCvcG68uiac/Ozc/szKoNh6sdtfyehao44cryjDwG+MuiN7zre4Rr0xsoGvfEBVFn6q3BeSr4o9qykgtiXoc+giEqehRjFxccCkRRjlML2f/IxFz/kj+FcEt+RY+2ZFi6P/ezn64zzaIu7gNhxWzfX3wvbyJTjo8OCgjHH3xNPbhIcf75XuLxmlEFv1NmCOMfaNZ0Bk0FvvNVWmM++fwuD3jgNdYMzz3ZdFuu1POivCBISdFQwtlLWL9u+LOmM+19dvo63VSd05frc3101RXDOMinoAz0EmGobpXFiUKtb1kTdXX7q0vwQzsWyGqMm5J006I37bZk5/6ImxU4wW0zr3Lx2PBcf4dTFudS3Yz/6o9IZTwH9zRaTu0mkDVyOKWhuhGuRtCYF7Oc6MuDuQ8dxSL5ZAefB9girFyptdoDZYnK8W7dXXHVc1j0UlTr9r0FvTDXojQdRa8vMtb3Oow6PZzw12qA3dnDTt0q2vgF8WtIRJLPFlIYqx2+fLHuvQW98o6gPNltwN4OLH/CngD62R47ubOTinCId8K1Bb3zIoDe2N+iNvQx64yeo3ynHmig3GfTGB22F6uwc5wR1RGWZGQx6Y2uDWlPoV5d97jDojVcb9MaBLoHOpQ7/dvpgL4Dj6FQ72/l0Br2xLWrZAnug+RDOE6dboWqtnDbojfsMemMGat7VI6jib6NK8VqiHNBZrd6q1isCmW3G//WoDIC2ts2bUfn+e2zD50WdoyaqSuU0VEaLIxPqDXSjffTEoDcORi0sZveY2WJyCgpsb+aLUatf5m82W0xbHfa5l4tD2L+hikhtRg2z34h65FMTGGq2mBw/FO3Ht0INBbtmHNhlA2PNFtM7BbRjSwl8B/WMPRRV9nkSal2JmqhVY8ehVvO812wx7XA5PgJVQj4BtcS43RTbnzSzxXTO9qiqNuqOf5zDfuttr/2PrXBYJVQdkpdwnmPwLer/Yb/D/0M9VHGpLrZ9lqOCs+2oD9/LUXNzYlE/55HmAlZgtb3uHGBQQT8rVArno2bnBe+KZNAbz6EC05PABNv3chL1QTYRFXQsAu4r7WMrg97Y3nYu+0Jo64FnzRaTyc2+BlRqtn1BvP1AP7PF9Kfrvi7H9UcVUXM3SrUf9f8WAfxs23be9u8VZospwXaOa1Gl7t2NTqShJoOnoP4vHQOnw6j/70jbPo5r9GSggoUNwHF3P0vbdbkd50ylLNSjkIFmi2mVw749UD9L19oljtag/t80I1TFeS0R/CToqCAMaln0AlcgNVtMRd3p1cazAkgvoj7U3kbVAHEcTbOihu0/M1tM821ByfNoUzAzUW9Sj5otpiMuQYejPNTd5PfAGwWUiLb3vwpqqfgBqA/rSNQjkERgilkt2FYk293XcFTg0Bj1gXIEFQQtARa4myRn0BvXcXH5c3emmi2mRw2q0uqIQvbbbraYOhj0xlEUvkDXGrPFdLNLH7qh7vJ7oB6L1UL9rA+ilk3/3La+SZEMemNPVJDSFTX6cx6V6bMS+MRsMRW5ZLubc9qDDldnUBNZPzNbTF8W97yFvF4l1OOwOC4WutqJCqDTUD8fIxd/Pw+hRjveLSgoc/Ma16PWJ+mCKi63BzVa9JGt/P41qKJ7XwLfmC2ms27OYUAtANgRFaTsQQXqH5ltawEZ9MYxqMAiFDU6MAY16lZg0T+bBLPFNLqAvjdDLaR4HWpk50fgVXejV7YbkidQVYAvR002Poq6SZhtm/RdoOK8lghuEnQIISo8W3CwAPeTPl9GjWyZC5i/IYTwkAQdQghB/qOMn9CWu/+f2WIqKmtJCOEBmUgqhBCA2WL6FfXozPVObJBBb5zkhy4JUe7ISIcQQjgw6I2PoFJjXSdvJgDPFLC4oBDCAxJ0CCGEC4NaQPBTtGv2bEJl91i0RwkhiiJBhxBCuGFL5bwVlU30fzhn1iSiJp4moVLOpay3EB6QoEMIIYpgK+99HWrRv1aoomy1USmsVlSa58O2ir1CiAJI0CGEEEIIn5DsFSGEEEL4hAQdQgghhPAJCTqEEEII4RMSdAghhBDCJyToEEIIIYRPSNAhhBBCCJ+QoEMIIYQQPiFBhxBCCCF8QoIOIYQQQviEBB1CCCGE8AkJOoQQQgjhExJ0CCGEEMInJOgQQgghhE9I0CGEEEIIn5CgQwghhBA+IUGHEEIIIXxCgg4hhBBC+IQEHUIIIYTwCQk6hBBCCOETEnQIIYQQwick6BBCCCGET0jQIYQQQgifkKBDCCGEED4hQYcQQgghfEKCDiGEEEL4hAQdQgghhPCJoA86dDpdmE6na6rT6cL83RchRPHJNSxExRH0QUebVu3+Avbt27cvG7DKn+D5M6D/QOuA/gP93g/5U/L/P4PeuINSkms4uP/IdRzcf7x1HXsq6IMOIYQQQgQHCTqEEEII4RMSdAghhBDCJyToEEIIIYRPSNAhhBBCCJ+QoEMIIYQQPqGzWq3+7kOp6HS6pqh0O5o2bern3ghR4ehKfQK5hoXwt1Jfx56SkQ4hhBBC+IQEHUIIIYTwCQk6hBBCCOETEnQIIYQQwick6BBCCCGET0jQIYQQQgifkKBDCCGEqKhyc336chJ0CCFK5osv/N0DIURpHD4M11/v05eUoEMIUTw5OfD00zBkiL97IoQoqc2boWNH2LjRpy8b5tNXE0IEt/R0uOce+P57f/dECFFSX3wBw4fD+fM+f2kZ6RBCeObPP8FolIBDiGDlOErph4ADZKRDCOGJpUth8GA4e9bfPRFClESAjFLKSIcQomB5eTBxItx1lzbgqF/fP30SQhRPYaOUTz7p065I0CGEcC8jA+6+G155RdvWqRNs2eLzLgkhimnpUujcGfbudd5eqRLMmgUJCT7tjgQdQgitvXvh2mvVG5arIUMgKQkaNPB9v4QQnsnLg/h496OUl1yiruFhw3zeLZnTUYT163/mqbini3XM9z8mUrNmjbLpkBBl7YcfYOBA9QzYUUgIvPsuxMWBTuefvpVASa7hkY89yqeffObx/hEREWz4dX1xuyZE2cjIUDcH7m4aOnVS2y+91Pf9AnRWq9UvL+wtOp2uKbBv3759NG3a1Ovnz8zMJOVQCidOnuSP3/9g9qw5ZGVlOe1Tq3Ythgx5kFatWlKtenWaNbuM0NBQr/dFiDJltaqh1mef1VYprFkTFiyAm25yParU0UcgXsN16tQmLS2N48fT2WLawry5X5Lr8jNp3LgxDwy+n+aXN6dadDTNmjfzet+FKLa9e+H229U8DldDhsBnn0GVKq4tPruLkJGOIlStWpUrWlwBQKdORs6dO8esmbOd9nlx7AvccEMPn/dNCK85dw4efRQ+/1zb1rYtfPMNNG/u+355QUmv4Ro1agBw7bVdSEtLY/WqNU7tb771Oi1btiyjXgtRAgWNUoaGqlHKJ5/0+yilzOkoptZtWmu26fUdfN8RIbzlv/+ge3f3Acedd6qKhUEacLhTkmu4TZs2Tl9XrVpVAg4ROKxWmDIFevfWBhw1a8Lq1QHzWLTMgg6D3niDQW+8razO7y9RUVGabdWqVfNDT4Twgt9+U6WQN2/Wtr3yCixaBNHRPu9WWSrJNex6THS18vUzEUHs3Dk1IfSpp7SPRdu1A5PJ3WNRv/H64xWD3ng18AbQC5gIfFvAfqHAE8BQoCWQDWwF3jZbTCu93S9vCQnRxmnutgkR8GbPVo9ULlxw3h4ZCXPnqlGOcqgk17AuxPkOMUQn17wIAP/9p65TdzcNd96pyp27CbL9yWtBh0FvrAEMB+oCnYvYVwfMB/oDOUAoUAXoDnQ36I1Pmi2mD73VNyGEg5wcNVnUXX5+s2Zq/ka7dr7vlxDCc7/9ptJhDx/Wtk2cCC+9pDLOAow3e3TKbDG9ZbaYngVWFbHvI0BboAcQAUQBfQF79ZK3DXqjFAEQwtuOH1fPfd0FHDfdpIZiJeAQIrDNnq3mYbkGHFFRKh12/PiADDjAiyMdZovJMff2XBG7jwT6mC2m/bavc4DvDHrjv4AFqAz0AWZ4q39CVHh//KFS6fbt07aNHg1vvw1hktAmRMDKzlajlB98oG0LklFKn4dCBr2xJbDWIeDIZ7aYdgD22sq1fNkvIcq1xYuhSxdtwFG5MsyZA++/LwGHEIHs+HG4+Wb3AUcQjVL6Y/xlL2qCaUEO2P7+1wd9EaJ8y8uDCRPUGioFlUIeMsQ/fRNCeOaPP9SCbT/+qG176ilYtQpiYnzfrxLw+a2N2WLKRmWqFKQ+cB5I9E2PhCinMjLUcvTffKNtu+YaWLLEb6WQhRAeWrxY3Ri43jRUrgzTpsGDD/qnXyUUUOOpBr2xMtAB+MJsMR0vzrGPPfo4kZGRmu0LFy/wTueECCb//AN33AE7dmjbhg2DTz5xVwrZrQH9BxbY5s3rS65hIRzk5alaOa++qm279FI1YbRTJ49P56vruCgBFXQAd6FGQV70d0eECFpr18I998DJk87bQ0PV3I1RowKiMqEQogCnT6tRym/dlLnq3FmNUl5yie/75QUBE3QY9MZI4FVgUHFHOQA++ezjMlksSoigYS+F/Oyz6i7JUUwMLFwIN95Y7NP66i5IrmEhUKOUt98Of/2lbXvoITVKWblysU8bKCOGARN0AB8Bb5ktpu/93REhgk5WFowYoSqJurrySli2TKXUCSECV2GjlFOmwOOPB/0oZUAEHQa98SXgb7PFNM3ffREi6KSkqJLHJpO2rX9/lRIbYKWQhRAOrFb16PO557SjlLVqwYIFJRqlDER+L1lm0BsfBqqbLabX/d0XIYLOxo1qwTZ3AUd8vHqzkoBDiMCVlaUyUJ55RhtwXHWVurbLScABfg46DHrjQMBotpieK6D9Vh93SYjgMWsW9OgBqanO26Oi1OOUl18O2FLIQgjg0CHo1g3mzdO29e8Pv/wCl13m+36VobJ6vBJh+7vAdzyD3tgHuAMY7KYtEngacLOSjRAVXHY2PP00fPSRtq15c1WXo21b3/dLCOG5X39VC7alpWnbXn0Vxo0L+vkb7pTF0va1gOtsX3Y16I1hZospx2Wf64HFQCVgoEFvdD1NKHAWVShMCGF37BgMGADr1mnbevaEr78OmsqEQlRYM2bAY4+pGwhH0dFq1OO22/zTLx/w2tirQW8MNeiNW1Dly+1lDm8E/jPojUsd9msBrECNhoQW8AdgvtliOuOt/gkR9LZvV6WQ3QUczzwD330nAYcQgSw7W9XJeeQRbcBx+eVqufpyHHCAd1eZzQU6erDfbqC6t17X1/JyczXbcnNzCQ0NdbO3EF6ycCEMHQqZmc7bK1eG6dNVISHhkZJcw3m5zhP88vK05xCiUEePwsCB7m8aevVSo5Q1a/q8W74ms8yK6eSpU9ptrjnVQnhLXp6aEDpwoDbgaNAAfv5ZAo5iKsk1fMrlmJOnTmG1Wr3ZLVGebdtW8Cjlc8+pUcoKEHCABB3Ftm3rNs22Tb9t8n1HRPl3+rRaP+W117RtXbrAli3qjUwUS0muYYvF4vT1+XPn2bZtuze7JcqrhQuha1f412Xh9MqVVTG/t95Sxb8qiIAoDhbIMjMzSTmUwrHjxzFtNrFo8WLNPm+/9S6pqWlc1f4qqlevTrNml8njFlE6f/+tSiEnJ2vbYmPh449LVAq5IirJNVynTm3S0tI4cuQoPyf9zM/rN2iOGffiOAY/OJhWrVpSo0YNLmtWvlIbRSnl5cH48TBpkratYUO1YFvHImcklDu6YB8i1Ol0TYF9+/btK5N1G9av/5mn4p4u1jHf/5hIzZo1vN4XUUGsWQP33hsspZBL3ZFAvIZHPvYon37ymcf7R0REsOHX9cXtmiivTp2CBx6AFSu0bddeq5arrx9QyZk+e0ORoEOUK2lpacyYMYOkpCQyMjKIjo6mR48exMbGUq9ePX93r3BWK7z7LowZ474U8sKFcMMN/ulbwQI+6BDCp3bvVqOUO3dq2x5+WNXXCbxRSgk6PCVvWAIgKyuLuLg45syZQ7ZrKhoQHh7OsGHDSEhIoEqVKn7oYRGyslQa3ZdfatuuukoV/ArM328JOoSwW71ajVK6TlYOC4OEBBg5MpBGKR35rFMyp0MEvaysLPr06UNSUhIAbRq2oWf7XsREx5Cekc7a7WtIPpTMtGnT2LVrF6tWrSIiIqKIs/rQwYNqwTazWdt2991qwbbISJ93SwjhIasV3nkHXnhBO0pZuzYsWgTdu/unbwFGgg4R9OLi4khKSiKyciTjB47H0Nx5clY/Yz/Me7YQvyCepKQkRo8ezdSpU/3UWxe//KJKIR854rxdp1OlkMeODdQ7IyEEqFHKhx+Gr77StrVvr0YpmzTxfb8ClKTMiqCWmprKnDlzANwGHHaG5h0ZP3A8ALNnzybN3XoHvjZ9upqj4RpwREerN6pyuvaCEOXGwYNw3XXuA46BA9VNhQQcTiToEEFt5syZZGdn07ph6wIDDjtD8460atCa7OxsZs6c6aMeumEvhTx8uPtSyJs2Qb9+/umbEMIzGzaolNetW52363Tw+uuqwqg8FtWQoEMENfs8jl7te3u0f+8Oar917ioD+sLRo2phto8/1rb17g2bN0Pr1r7vlxDCc9OmwY03uh+l/PZbePFFGaUsgAQdIqhlZGQAEBPt2UJnMVE1nY7zqW3b1J2RLVBy8txzsHJlhSmFLERQunBBrQ47YoR2lLJFC3XTcOut/ulbkJCJpCKoRUdHA5Ceke7R/ulnTjgd5zMLFqgF27KynLdXqaKWub7/ft/2RwhRPEeOwIABsN5NEbg+fdS8jho1fN6tYCMjHSKodbeloa3dvsaj/ddsU/v16NGjrLrkLC9PTQi95x5twNGwoVqwTQIOIQKbxaJGKd0FHGPGwPLlEnB4SIIOEdRiY2MJDw8n+VAy5j1bCt3XvGcLO1OSCQ8PJzY2tuw7d+qUqkz4+uvatq5dwWSqkGsvCBFUvv5aXa8HDzpvr1JFjW68+WaFWrCttCToEEGtfv36DB06FID4BfEFBh72Oh0Aw4YNK/uS6Lt3wzXXuF974ZFH4McfA23tBSGEo9xcNSF00CDtKGWjRioddtAg//QtiEkZdBH0XCuStm7Yml7texMTVZP0MydYs20NO1PUaq3du3dn9erVZVsKfdUq9WbkrhTyBx/Ao4+Wp5ntUgZdlD+nTsF998F332nbrrtOLdhWt67v+1V2pAy6EJ6KiIhg1apVjB49mtmzZ5N8KJnkQ85Lwvtk7RWrFd5+W5VCdg3mpRSyEMFh1y71WHTXLm3bo4+qNVQqVfJ9v8oJGekQ5UpaWhozZ85k3bp1vl1lNjNTlUL+3/+0bR06wLJl5bUyoYx0iPLju+/UKOXp087bw8Lgww9V0FE+ySqznpI3LOF3Bw6oBdtcKxOCKoU8a1Z5rkwoQYcIflYrTJ6s1jpy/UysU0c9Trn+ev/0zTfk8YoQgSQtLY0ZM2aQlJTkNILyaLt2xDzyiPsF2yZNUo9ays/8DSHKn8xMeOghmD9f23b11bB0KTRu7Pt+lVMSdAhRiKysLOLi4pgzZw7ZLhUIL0tMJMrdQdWqqVS6vn190kchRAn9+68apbRYtG2DBqnCfVWr+r5f5ZgEHUIUwDUrpk3DNvRs34vaVatxw6aldD3wh/agFi3UCrGtWvm4t0KIYlm/Hvr3h2PHnLfrdKr2xnPPyShlGZCgQ4gCxMXFkZSURGTlSMYPHI+heUfCz5zgygUTqekm4PijUSOu3LRJKhMKEeg+/RSefBJycpy3V6+uRilvucU//aoApDiYEG6kpqYyZ84cgPyAI/q/3XSa9pjbgONNwHj4MGnnz/u2o0IIz124oBZre+wxbcDRsqVasE0CjjIlQYcQbsycOZPs7GxaN2yNoXlH6v3xI4ZZo6ly2nnCaG5YJf7sP47PG7TmfE4OM2fO9FOPhRCFSktTy9FPm6Zt69sXNm1Sj0dFmZKgQwg37PM4el/Vk+bfz6Dd4kmE5jiPYpyrVhfzQwmkXXkjvTv0BmDdunW+7qoQoihms1rn6JdftG1jx6p5WNWr+75fFZDM6RDCjYyMDKoBj1lW0fTw35r2k43b8fvAV8iOqglAjO3vjIwMX3ZTCFGUr76C2Fg4d855e0QEzJ6tVoAWPiNBhxButAkJYQ5whZuA41DHfuy++XGsYeH529LPnAAgOjraRz0UQhTKvmDb229r2xo3VqMbHTr4vFsVnQQdQrhauZKPzWZcV2jJCwlld58nSDH20xyyZtsaAHr06FH2/RNCFO7ECbVg2+rV2rZu3dQ6SHXq+L5fQuZ0CJHPalX5+f36UcUlC+VC1RpYhrzjNuAw79nCzpRkwsPDiY2N9VVvhRDuJCfDNde4Dzgefxy+/14CDj+SkQ4hoNBSyNt0IWy8+VFaNLlK02bes4X4BfEADBs2rGwXlRNCFG75crj/fnCdWxUeDh9/DI884p9+iXwSdAjx779wxx2wbZum6Yc6deh39ChZS96k9eZv6NW+NzFRNUk/c4I129awMyUZgO7du5OQkODbfgshFKsVXn8dXn5Zu2BbvXpqwbauXf3TN+FEgg5RsRVRCvnaUaMY/NRTzJ49m+RDySQfSnbaLTw8nGHDhpGQkECVKq6zQIQQUPCCibGxsaUfHTx7FoYNg4ULtW0Gg1qwrVGj0r2G8BpZ2l5UXMUohZyWlsbMmTNZt26d9980g5ssbS8KVNiCieCFoH3/frj9dvj9d23b/ffD9OkqNVYUxWeLzEjQISqeCxfgiSfcVyZs2VKl0rVs6ft+BScJOiqookYvClowMSY6hvSMdNZuX5M/cti9e3dWrVpFRESE56Mi69bB3XfD8ePOHQsJgcmT4ZlnZME2z0nQ4Sl5wxLFkpamHqe4q0zYty98+aVUJiweCToqGE9HL3Jycpg1a5bTgomu7BOxz54/y0MPPURoaGjRoyJTplBl5kwYPVrV4nBUowZ8/TX07u2l77bCkKDDU/KGJTxmNqsJo4cOadtefBFefRVCQ33erSAnQUcFUpzRC51Oh9VqZfLgyW4DDjvzni2MmTsmf//CzlsJWFK/Pn1TU7Unat1ajVJecYXXv+8KwGdBh0wkFRWDlEIWotTi4uJISkoqcPSin7Ef5j1beOmrl8jOvbhgYmEMzTtSvWoNTmWepGrlqkwYOMHteXf+8SOGJW/Q2V3A0a8fzJsH1aqV+nsUZUuKg4nyLTcXnn9eTSpzDTgaN1aPWSTgEKJIqampzJkzB6DAxyWggoimdZsC0Kt90Y850jPSycg6DeA24ACITtlJ7NqpdLbmaU/w8suwbJkEHEFCRjpE+SWlkIXwmpkzZ5Kd7dnoRVio+miJiY4p8ryrLKvIs+YVeN762xNp9e27hOY6z/O4EB5Opa++UpNJRdCQoEN4RZnm4ZdEcrJKpftbu2Abjz0GU6aoKoVCCI/Y53F4MnpRtVJVQI1iFOX3/dvdnleXm0vz76fRZOMizTH7gMkGA59JwBF0JOgQpVLYTPbExEReeeUV3xfPKqwU8kcfwfDhvumHEEGmsJuHDNv15MnoxVVN22Pea2bt9jX0c7NekaPMC5ma84Zlnqbdoteotdes2X9f3cswHtnHFUX0t4LXzwlYEnSIEvN0Jvu0adPYtWtXfh5+mbFa4Y034KWXtKWQ69ZVpZCvu67sXl+IIOXJzUPdunUBz0Yv+uj78PlPc0g+lIx5z5ZCH8fk5OY4nTfyyH6u+t/LVD3xn2bfg53u5MNaDTm+6kOqHDxIo0aNAudmR3hEgg5RYp7OZI9fEE9SUhKjR49m6tSpZdMZKYUsRIl4evOQkpICwOptq4ocvYiJjiE6ohqnMk8yccHEAieImvdsYf+R/QCs3b6GYdExtF3yBmEXspz2ywsNZ2ffOA5f3YdV00cB5PfH7zc7olikTocokdTUVBo3bkx2drbHefjh4eEcPHjQ+8Oe+/er+hvbt2vb7rsPZsyQUshlR+p0BLnhw4czffr0Iot4TVwQT+b5swAlqr3RumHrAhdMDAHGAfFuznU+Kobf73mF043a5p8X1LyRCfcUHMzYi44NHz687G52yg+f1emQlFlRIsWZyW5o3pFWDVqTnZ3NzJkzvduRdevAaNQGHCEh8PbbKndfAg4h3CpOGuyEgePzv544fyLmPVvc7mv/wAcYNmwYw4cPJzw8nORDySSsnMKE+RNIWDmFnSnJhIeH88SwYWxu0sRtwHHq0paYhn+SH3BMXHBxr4ICDnt/x9v6O3v2bNLS0or6UQgfkccrokSKM5MdoHeH3uxMSWbdunWMHTu29B2wWuGTTyAuTlsKuXp1VQr55ptL/zpClGMluXnYmZJM5oVMxswdU+joRffu3fn444+pUqUK8fHxbhdMHH7TTdR++GH491/N621u0JrELv05uus3p/MCtGzQslj9nTlzpnfed0SpSdAhSqQ4M9kBYqJqOh1XKufPw6hR6rGJq1atVCnkFi1K/zpClHMlvXlo0KABR44cIflQcn7Zczt3K8fWq1ePsWPHOn/w//AD9OkD6c4TU3OBZ4CElGRY9JrTeevWrUtKSgo3d+hTrP567WZHlJoEHaJEoqOjAc9msgOknznhdFyJpaaqBdt+/VXbduutasE2qUwohEdKevPQqFEjzGaz29GLItNVrVb48EN4+mntKGXNmpz+7DPq/vMPPd2c94477iAlJcU/NzvCKyToECXSvXt3EhMTPcrDB1izbQ0APXr0KPZr2XPxD3/7LeO3baPuhQvancaNg/h4NZdDCOGR0tw8uB29KMq5czByJNjmkThp2xa++YaazZszFtye1283O8Jr5B1alEhsbGz+5LCCJpTZmfdsyZ80Fhsb6/FrZGVlMXz4cBo1akTySy/xzubNmoDjfFgYF+bNg9dek4BDiGLq3r07oNJVPVGamwf++w969HAfcNxxB2zcCM2bF3oKn/ZXlAl5lxYlUr9+fYYOHQpA/IJ4j2eye5oua68dMHP6dCZlZzMPcC3xsx/olJNDr+nTycrK0p5ECFEoX9w8ALBpE3TsqP52NWGCKtznwWiEz/oryowEHaLEEhIS6N69O2fPn2XM3DE8MWMUy03L+SV5A8tNyxk1fRRj5o7h7PmzdO/enYSEBI/PHRcXx/akJNboQnnOTfuJpu1ZPuBl9lSOzC88JoRwlpaWxqRJk+jVqxddunShV69evP766/kppGV98wCokY1u3eDwYeftkZEq2HjlFY9HKX3SX1GmpDiYKJWsrCxGjx7N7NmzNeWIwf1M9qKkpqbSu1EjFuXkcIWb9oOd7uDv3iOxhoaVfeExURQpDhaACitrDs7XpdVqdapIWlQa7OrVqz27lnNy4Nlnwd3NxmWXqSyzK68s0fdW0v7KWi0F8llxML8HHQa98S5gBBANhNv+/haIN1tMZ4o6Xt6wAkNaWprHM9mLuvAXPPAAfb78EtfB1ryQMHb1fZL/DH2dto+aPoqdKclMmjRJ0uJ8T4KOAONpWXNQH8qrVq0C8O7Nw/HjcM89Ki3W1f/9H8yfD7Vqlep7LE5/ixOEVdC1WipG0GHQGz8A7gd6mS0ms21bM2A1cAboaraYCn1YL29YwaOoC79SWBgLOnTg9i3aIdPzkTX5456JnGrcVtO23LSchJVT6NmzJ2vXri2TvosCSdARYDwta+6uTHhxbh4K9McfcPvtsG+ftm30aFUpOMw7iZOe9LckQVgFXKul/AcdBr2xC/ArakRjgkvbAGABEGe2mD4o7DzyhhUcirrwN1hW8cJ/u7jbzbGnL23J7/dM5Hz1Om7P/UvyBibMn0Dnzp3ZuHFjGX4Xwg0JOgKI39dEWrIEHnxQLcDoqFIlmDoVbPMxfKk0QVgFUiHWXrne9re7hOs/bX+39lFfRBlzXJF28uDJfPDwh/Qz9qNrq64MuLwjP+VccBtwHL7qJszD3i8w4ADJxRfCzm9rIuXlqQmh/ftrA45LLoH16/0ScBRnbRlZq8U3/Bl02EvEuatn29D2t5vxORFsCrvwa+61YJz2GNFHnP+rc4HJ1evy150vkBdeudDzSy6+EEpJypoDrFu3ruQvmpGhgo2JE7Vt11wDW7aov/0gYBamFPn8GXSsRn229DbojXH2jQa9UQeMBo4A8j9fDri98K1WGm5aSoe5z1Mp67TT/qd0IfQBXjh1BPNec6Hnllx8IS7y+ZpIe/ZAly6wbJm2behQtQr0pZeW7Nxe4JcgTBTKb0GH2WLaB7xi+3KKQW+catAbLwE+B2qhJpEe91f/hPe4Xvi6nAu0/vYdWq76iBBrntO+Z+o04cPuD5Jo+1py8YXwnE/LhCcmgtEIO3Y4bw8NVWmys2aBnzNB/LowpXDLr2uvmC2m1wx6YxgwARgOPAzMB641W0x5hR7s4rFHHycyMlKzfeHiBd7oqigFxwu/UsZxrpo/geouK1MCHG15LTvuepG8vVsB9UaYkZHh0RLaxSk8JopnQP+BBbZ58/qSa7j0fLImktUKU6aoGhx5Lm/TMTGwYIFKiw0AslbLRb66josSCAu+TQSuBvqhRl4GAScMeuNos8WkzasUQcd+AUcd/AvjygSqZGgHsPZ1e4C9PYZASEj+hW80Grn88suZPXu2x0toF4cUChLlTWxsLBMnTswvE15U9kqxH02eOwcjRsAXX2jbrrxSPWZp1qxknS8DvlyYUnjG33U6IoF5QB7qUcsnwHW25lXA7UUFHpJuF/gmTZrErpdeYjo6KuP8+5YTXoW/7hzD0Tbd8re5FvvySu0AB1IoyKskZTbAlFmKaEoK3HknmEzatrvugs8/h6goL3wH3uP3FOLgUSHqdIQAPwB1AIPZYjpv2zYONfqhA8aaLaY3CjuPvGEFuJwczj7+OJHTpmmasmrU5/d74zlT/+LKkmV94UuhIK+ToCPAlKZMeIE2blSBRWqqti0+HsaNC9hVnqVOh0cqRNBxN7AQeMJsMX3k0jYOeA1IM1tM9Qs7j7xhBbD0dFUK+fvvtU1NO/DngPFkR1bP3+aLC1/egLxOgo4A5NU1kWbNgpEj4cIF5+1RUTBvnqo+GsDKJAgrfypE0PE+KjX2ZrPFtMalrRLwHyqLpZbZYipwFpC8YQWoP/9Ub0Z792qaEoCZDVpxY4ebfXrhy1BrmZCgI4CV6tFkdjY88wx8+KG2rXlztWBbW+2yBIGoLBamLGd8FnT4cyJpqO3vuq4NZovpgkFv3IsKOnJ82itRekuXwuDBmsqE1kqV+KJLF5779VeyU3byR8pOp/ayvvBLUihoZ0oyM2fOlIXkRFCqV68eY8eOLf7v77FjMHAg/PSTtq1nT/j6a5WpEiQiIiKYOnUq8fHxXp0fJorPn0HHauAJ4GZgrmODbaSjGfCr2WI67eZY4SBgsjDy8uC112DCBG1b/froli5lSOfO3OzliaGeKkmhoJ0pyaxbt06CDhEwyvx6374d7rgD9u/Xtj3zDLz5ptcWbPO1Egdhwmv8nb0yB3gQeBL42GwxWQ16Y2XgA2Ag0MNsMW0v7BwVeWg2oLIwzpyBIUPUgk+uOnVS2xs0KNs+FKFLly789ttvTLw3nq6tuha5vywk5xF5vOIjPrneFy1S13FmpvP2ypVh+nQ1ginKowrxeAWzxTTUoDf+AIwAnjbojf8BVYAtQHuzxXTAn/0LZJ5mYUybNo1du3aVbRbG3r1q/saff2rbhgyBzz7ze2VCkEJBIniV+fWel6dGKF97TdvWoIF6ZGo0eum7ERWZ38fIzBbTXFwer4iiOa7a6i4Lo5+xX34WRlJSEqNHjy6bLIwfflDPftNdPshDQuDddyEuDnQ+C6ILJYWCRLAq0+v99Gl44AFYvlzb1qWLGqWsX2gSoRAe8+vjFW+oiEOzAZGFYbXCBx+oZ7y5uc5tNWuqUsg33eSd1/KSgPi5lT/yeKWMlenv7d9/q1HKZO2yBMTGwscfq0crorzz2Z1hYFZzEYXy+3LN587BsGEwerQ24GjbVlUsDLCAA6B+/foMHToUkIXkRPAos+t9zRo138o14AgNVWmy06dLwCG8zu+PV0Tx+SoLw90s+VuvvpqRa9cSbrFoD7jjDrUmQwDPgUhISGD37t0kJSXJQnIiKHj9erda1aPPMWO0C7bVqqUmk8ojRVFGJOgIQmW9XHNBs+SvAe5OTCTc3UGvvAIvvxywpZDtIiIiWLVqVX6hoLJYSE4Ib/Lq9Z6VBY88Al9+qW276ipV8EsecYkyJEFHECrLLIyCZsnfcPRf+m75lrA858cp1shIdHPnqoWggoQUChLBxGvX+8GD6jo1m7UHDRgAs2dDZGSp+ipEUQL7tlS41b17dwDWbl9TxJ5KcbIwHGfJTx48mQ+HTeHpYwe4ffNSTcCxB4jv0yeoAg5H9kJBa9euZePGjaxdu5axY8dKwCECileu919+gY4dtQGHTgeTJsH8+RJwCJ+QoCMIxcbGEh4eTvKh5AInQ9qZ92xhZ0oy4eHhxMbGFrpvamoqc+bMAWD8wPFcc8kVdJg3hsabtAW/9te/HCMw6ZtvSEtLK+m3IoQoQqmv9+nT4YYb4MgR552jo9XjlLFjAyatXZR/EnQEobLKwnCcJd8tKoZO0x4nZp92wuiBzv3Z+8gn1PN2VowQQqPE13tMDDz+OAwfrhZvc3TFFbBpE/Qrul6NEN4kdTqCVFks19yrVy8SExOZefWtPPjH94Rln3NqzwsNZ+etozmsvxmA5ablJKycQs+ePVm7dm0ZfJciCEidDh8o9vU+dy5VHngA1q/Xnqx3b/jf/1Q9HSGUilEGXZRcWWRhnDl9mleAh7au0LSdj6rF7/dO5HTD1vnbipsVI4QomeJc7x889BCVr7sODrhZReK55+CNN1QtDiH8QIKOIObVLIyMDN7Zu5dr3TSdatCa3+95hQvVajttl7VJhPAdj673devU/I2sLOeDq1SBGTPg/vv90nch7OTxioA9e1Qp5B07NE3/dejNrr6jyQuvpGkbNX0UO1OSmTRpkiwVXXHJ45VAkJur6uS88Ya2rWFDWLYMDAafd0sEDXm8InwkMRHuuQdOnHDanKcL4e/eIzl0zZ1uZ7YXJytGCFGGTp1SIxgrV2rbunaFxYtB0sBFgJDslYrKaoX334ebb9YEHMeBfmGV+KZO4wIDDlmbRIgAsGsXXHON+4Bj+HD48UcJOERAkZGOiujcORgxQq2T4iKvXTtGVa3Kd5s3852sTSJE4Fq1CgYNUiMdjsLC1IJtjz7qn34JUQgJOiqalBRVQdRk0rbddRchn3/OrNBQqpXntUmsVsg8CKd2QMY/kJMJ1tyij6soQsIhvBpUawXV20KV2kUfI3zHaoW33oIXX1T/dlS7tnqc0q2bf/rmS9ln4NRfcPovOH8ccs/7u0eBQ6eD0AiIbALV20BUcwgJjI97mUhakWzcCHfdBamp2rb4eBg3zmnBtrS0tPK3NonVCinL4dhmsGZDaFUIqwY6edKYz5oDF06ov0MrQcM7IUZf0N4ykdSXMjMhNha+/lrb1qGDmjDapImve+V7Zw/Cvi9U4IEVKtWCEO1k94orD3Kz4MJJFWxENYfLHoDQygUd4LOJpBJ0VBSzZsHIkXDhgvP2qCiYN09lr1QE/62CIz9D5XpQtxtUrisloN2x5sLZA5D2gwo+mgyEGu3c7SlBhxekpaUxY8YMkpKSCg7wDxyAO+4Ai7ZKMPfco67xqlV92m+/yEqFPTMh5yzU7QHRLSTgKMiFk5BugtPJEH0FNB9W0A2WZK8IL8nOhmeeUc94XTVvrtZeaNvW9/3yh5wsNcIRXlPdvQfIcGNA0oVC1GVQeQDsnwdHNxQUdIhSyMrKIi4ujjlz5pDtUqo8MTGRV155RRX8GjCAyvfdB0ePOp9Ap4PXX4cxYypO8HzcBBdOQ8M71OMDUbBKNaDeTWDNgzP/qMfKfv6ZybtueXbsGAwcCD/9pG3r2VMN0cbE+L5f/pKxC/LOQa3OEnB4Krw6RDaDzH3qkUslKZ3tLa6lzds0bEPP9r2IiY4hPSOdtdvXkHwoGd20aYROn66dv1GtGnz1FfTt64fe+4k1T83jqFTD7x+eQUOng5p6yNgJJ3f4/ecm77zl1fbtaih2/35t29NPw+TJapZ7RZKZAnm5ENnU3z0JLlFNbXdJKRJ0eFFcXBxJSUlEVo5k/MDxGJp3dGq/TX8zMfMn0OHvTdqAo0UL+PZbaNnShz0OABdOQE4GVGvj754El8p1IKQKZKX4uycSdJRLixbBkCFq0pmjypXVMteDB/unX/6Wew6wqlndwnOhVQGr7ecnvCE1NZU5c+YAuA04Kp1J58oFE6lx4E/twbfcAl9+CTVqlH1HA03ueRWAyTVcPDqdmkQaANewTNkvT/LyVCnkAQO0Acell8LPP1fcgMORZKoUk32uQHBPOg8kM2fOJDs7m9YNW2sCjuj/dmOc9rjbgOPXbt3UCEdFDDiAi7+Dcg0XXwiBcA3LSEd5cfo0PPAALF+ubevSReXuX3KJ7/slhNCwz+Po1b630/Z6f/xI62/eJjTHOcvsQkgYD+blkF65MmtlhVgRxCRcLA/+/hs6d3YfcMTGqomkEnAIETAyMjIAiIm2TeTOy6V54jTaLZ6kCTjOVavLnP+LZb7DcUIEKxnpCEAe5ezbrVkD994LJ086bw8NhSlT4PHHK04qnRBBIjo6GoD0jHTCss7QdvFr1P5HWyX4ROMr+WPgBP5K3uB0nBDBSoKOAOJpzn5CQgJVKleGd99V+fl5ec4nqlULFi6EG27wYe9FIDqcepTIqhFUqxbl764IB927dycxMZG/t3yLceNCqqZrswoOdbyN3Tc/hjUsnDXb1gDQo0cPH/dU+Ft5u4Yl6AgQnubsT5s2jX1//cV3DRsS5q4U8lVXqVLIl13m229AeMXwJ8ZhtrjJWADen/wS3boaCzz2bGYmt9z1MGfOnM3f1rBBfZZ9/ZnTfn/v2c/nXy6hccNLOZhymEYNLiF2yABCZa6Az8TGxmKaMIHP0/biWkM0LySU3bc8QUrHfoBa1XlnSjLh4eHExsb6vrOiWOQaLpwEHQGiqJz9fsZ+mPdsYcb8V3h9wwb3/3F33w1z5kBkpC+6LLzsYMphjh5NZ8RDg6hS5eIaCUePHWfxN2swGq4q9PhvVnxPl04dqFe3Tv62a4zt0Tk8Xvtn7788/PhYPp0ykTatrsBqtfLks/G8kzCDMU+P8P43JbSsVurPmsWS3FzNpLoLkTX4feArnGpyJaACjvgF8QAMGzYseNc8qiDkGi6aBB0BoKicfbsbw6vwWEgobgfZXnsNxo6V+RtB7OdfTEz76DXq1K7ltH3e19/QuZOeiCoFLtZEbm4u3//0K1M/eJXw8PAC93t7ynRatWhGm1ZXAKDT6Xjw/jsZGTeeO/r1pOUVzbzzzQj3zp6Fhx6CBQs0AceO8CosvKY/IZmnSDctZ822NexMUSs8d+/enYSEBN/3VxSLXMNFk+yVAFBYzr7dpeaVXD3nGaLOnXFuiI5W66eMGycBR5C7b+BtmjcrgB+TNtLj+msKPfaHdRvZf+AQr07+mJWrf+Ksa50W4L/DaWzZ+geGDs5rqLRv15rQ0FC+WfF96b4BUbj9+6FrV1iwQNP0P50OY/Y5Jv44kwnzJ5Cwckr+I5Xhw4ezevVqqlSp4vs+i2KRa7hoMtIRAArK2QfQ5eZwxepPaGT6RtOWEhFBg02boHXrMu+jKJzVaiUry7Nqf7qQkELveBwdO36CHcl/896bYwvdb4vlD0J0Iaxc/RMrV/9E9erRvDI2zun58Z9//Q1Ao4bO6dOVKoVTr25tLNv/8qhPogSSktTjz2PHnLfrdDB5MjcOHsxLs2axbt26ojPWRJmQa9g3JOgIAJqcfZvwsye5ckE8Nf/drjlmNfBe27aslYDD62bPXcTcr5fxw4q5+c9Sn3hmIjk5OXya8KrbYw6nHqHfgOEenf+S+nVZsWi6R/v+tP432rdrRY3q1Qrdb+yzIxn77Ej2HzjEVwuWs+SbNTz/0ptM//B1rmyn1uc4cvQ4ANWra9Mua1SPZv8B/6/LUO5YrfDppxAXBzk5zm3Vq6tFF2++mXrA2LFjGTu28A8m4Rm5hgOXBB0BwDFn3y7q8D9c9fV4Ik6lafb/oZmBvnvN/F9NWXyrLJgtf9JR3y7/zerChWy2bt/BI0PvKfCY2rVimPHxGx6dv3Llgp/XuvopaSM9uhU+LOuoaeOGjH12JJ2NHXj+pcl8NusrPn5vIgAXLqiiU+Hh2su+UqVwzp+/oNkuSuH8eRg1CmbM0La1aqUei7Zo4ft+VQByDQcuCToCgD1nf+32NfQz9qPun+tos+wtQnPOO+2XG1aJ5NueYdSmZeQhOftlIScnl+1/JPPEyCH5237bbOHcufNcY+xQ4HGVKoWjb+/dlS9Pnz6DedsOXhrzeLGPvbF7F27o1tkpdc9+p5WTk6vZPycnl5o1Cr8TE8WQmgr9+8Ovv2rbbr0V5s1TIx3C6+QaDmwSdASA2NhYJk6cyM5DyVRd9BpX/vmTZp9z1erw+z0TWXcuQ3L2y1Dyrn/IzDrnlNr25YJvqVGjGq1aFDwrPC8vj7NntRO/3NGFhBAV6VqdQSvpl800a9qISy8p2TN9g74dv27amv917VpqZOz0aW0p7VOnMqhbRzsBTpTAli1wxx2Q4maoe9w4iI+HEJnDX1bkGg5sEnQEgPr16zPyvvu46fPP6eIm4DjZqC1/DHyFjUf2Ss5+Gdu6bQd1asdwWZOGgJp1npp2lGsMzrnyrlLTjnr9efBPHsx4L0x2dg4NG9TP/1rfvg1hYWEcPJTqvF9ODqlHjhZrCFgUYN48eOQROOcyIbFqVZg9GwYO9E+/KhC5hgObBB2BYPdu3v/tN7f5y+ZmBr5q0YXvvh4vOfs+YLb8SYer1OTc1LSj7D+QwuHUo8Q+OICjx45Tu1aM2zcubz8Pzso6x2+btzEidpDb9tzcXNJPnHSbnme3cdNWbr35xvyvo6OjuMbYnq3bdzjt98efu7hwIZveN3XzqP/CjdxceOEFeOcdbVuTJqpKcIcOvu5VhSTXcGCToMPfVq2CQYMIOXXKaXM28CTw2V4z7DUDEB4efnHtFcnZ97rc3Fy2/ZFMg0vqsf4XE0kbNmG8+ipyc3O5vHkTkjZs5u47+rg91tvPgzdsNFOrVo0CC/28+e5Ulq1IZPpHr5OZmcUrb3xA3949eDT2PipXrsSCxSsJrxTOoAH9nI4b+fD9PPz4iyTv/IfWrS7HarXy+VdL6PV/1xU69CwKceKEWnRx7VptW48eqi5HnTraNuF1cg0H/jUsQYe/WK3w9tvq7shqdWrKi4lh/l13sefff+ksOfs+s3P3XrBaOXU6g29WJDLhxSf5fcdOoqIiWbHqJ55+wndzaH5K2kj36woeKq1dqybRUZFERkZQr25tmjZqwPzFK/nlt620bXU5V+vb8d4bYzVrMbRu2ZxP3p/IjM8X0LRJQ44ePc7lzZrw6MP3lfW3VD799Rfcfjv884+2bdQoeO89KKS6pPAuuYYDn87q8oEXbHQ6XVNg3759+2jatKmfe+OhzEx4+GH43/+0be3bq1S6Jk3K5KXT0tKYMWMGSUlJFa8I0YHFcOw3aBEHOu3DrC++WoLJ/AcfvjvBD50LYGcPQMoyaNwfamkWqyp1GdygvIYBvv0W7r8fzrhUCQ4Ph08+Ude48K7MFNj9CcR0cve7KNdwYfZ9AeFVoeWT7lp9Vs5aRjp87cABuPNO2LpV2zZwIMyaVSYLtmVlZREXF8ecOXPIzs52aktMTOSVV16p8I9uzNt20P5KKbYmimC1wqRJ8PLL2rZ69WDJErj2Wt/3S8g1HAQk6PClDRtU7v6RI87bdTr1JvbCC2WyfkpWVhZ9+vTJL7fepmEberbvRUx0DOkZ6azdvobkQ8lMmzaNXbt2sWrVKiIiIrzej0B27vx5tmz9g8H33uHvrohAduYMDB0Kixdr2zp2hKVLoaHKmqjQo4p+INdwcJCgw1emTVPPeF1GGYiOhq++UgWDykhcXBxJSUlEVo50u4ptP2O//CW0k5KSGD16NFOnTi2z/gSitT9soHKlSlzVrpW/uyIC1b59av7GH39o2x54QF3jEREyqugncg0HB5nTUdYuXFDrLnz2mbatRQs1f6NV2V0kqampNG7cmOzsbCYPnlzgKrYA5j1bGDN3DOHh4Rw8eLD83Y0VMadDFEDmdMCPP6rHn8ePO28PCVETwp96CnQ6j0cVQaW+V8RRxVIpYk6HKITM6agAjhxRK0v+/LO2rU8fNcJRo0aZdmHmzJlkZ2fTumHrQgMOAEPzjrRq0JqdKcnMnDlTFp8SwmqFjz5SQUWuS+npGjVg/nzo1St/k4wqClE4ud0rKxaLesbrLuAYMwaWLy/zgAPIv+Pq1b63R/v37qD2W7duXVl1SYjgcP68ykB58kltwNGmDZhMTgFHamoqc+bMAXAbcNgZmndk/MDxAMyePZu0NO2ijkKUVxJ0lIWvv4auXeHgQeftVaqo0Y033wSX3OuykpGhavTHRMd4tH9MVE2n44SokA4fVoW9Zs3Stt1+O/z2G1x+udPmkowqZmdnM3PmTC92XIjAJkGHN+XmwosvwqBBkJXl3NaokcpeGeS+JG5ZiY6OBiA9I92j/dPPnHA6TogKZ/NmNUr522/atpdfVimxbq4PGVUUomgSdHjLqVNw221qFMPVddeplScNBp93q3v37gCs3b7Go/3XbFP79ejRo6y6JETg+uIL6NYN/vvPeXtkJCxaVOgKsTKqKETRJOjwhl274Jpr4LvvtG0jRsAPP5BmtTJp0iR69epFly5d6NWrF6+//nqZP8+NjY0lPDyc5EPJmPdsKXRf854t7ExJJjw8nNhY35ULFgVzTbkUZSQnB55+GoYMUXM5HDVtCr/+qmrsFEJGFUVB5Dq+SIKO0vruO+jUSQUejsLC4NNPyXr/fYaPGkWjRo146aWXSExM5LfffiMxMZFx48bRqFEjRowYwTnXpbC9pH79+gwdOhSA+AXxBQYe9hn1AMOGDSt/6bJB5uix47z57me8/Or7Hh+zdPlaJr7+AW9NmcajcS/zY9LGQvffuXsvnbrfVdquBr/0dJVN9r6bn/UNN6gJo1ddVeRpZFRRuJLrWEtSZkvKaoXJk2HsWM2CbdSpA4sWkWU0BkQl0ISEBHbv3k1SUhJj5o6hdcPW9Grfm5iomqSfOcGabWvYmXKxdkBCQoLX+yA8t2HjFtZv2Mzib9bQ/fqCF4xy9NWC5fz8y2Y+mRKPTqfj3wMpDBo2mgkvPuF2uevsnBzi3/iAXNesjIrmzz/VxNC9e7VtTz6plqr3cMG22NhYJk6cmD+qWFRNHBlVLN/kOnYv4EY6DHrjNQa9MdegN/bwd18KlJmpJoS++KI24NDr1fyNbt2ccvYnD57MBw9/SD9jP7q26ko/Yz8+fPgjJg+eTGTlyPyc/bIQERHBqlWrGD58eP6jloSVU5gwfwIJK6fkv/kNHz6c1atXS5VEP7uuS0eee2q4x/ufOp3BR1O/oHfPbuhsZfSbNG5Aj+s789aU6Zw/f0FzzBdfLqFmzepe63NQWroUOnfWBhyVKqmslYSEYq0QK6OKwpFcx+4FVNBh0BsrAbMIsH45OXBATQydP1/bdu+9KkOlceOAy9mPiIhg6tSpHDx4kEmTJtGzZ086d+5Mz549mTRpEgcPHmTq1KkScASI8DDPByF//W0r589foMGlzh9eHa5sxcmTp/nlN7PT9n/2/svZs1lc1baClovOy4OJE+Guu+DsWee2+vUhKQmGDSvRqRMSEujevTtnz59lzNwxPDFjFMtNy/kleQPLTcsZNX0UY+aO4ez5szKqWAHIdawVaI9XJgBX+LsTBVq/XlUYPXrUebtOB2+8Ac8/n79gW6BWAq1Xrx5jx46VaqNeZrVaycrybF6OLiSEiCqVvfbah9PU72Mll7vyevVqA/DXzn+4sXsXAHJzc5kxZz4TXnySL75a6rU+BI2MDDVZdKmb771TJ5UO26BBiU9vH1UcPXo0s2fPJvlQcn7Zc7vw8HBZeyVAyXVc9gIm6DDojXqgM7AR0D688rdPP1XPeHNynLdXr64Kft1yi9PmkuTs70xJZt26dRIQBIit23bw1YJv2ZH8N0ePpWNfp6j5ZY1ZMPdDp30Ppx6h3wDPhlIvqV+XFYume62f1aOjADh6zDlrwj4/6OTJ0/nb5n39DXfd1puIiAr4Ybd3r5q/8eef2rYhQ9T6SF4IAuyjivHx8cycOZN169bJKrN+JNdxYAmIoMOgN4YBHwNDgWn+7Y2LCxdUsOFufYSWLdWCbS1bapokZz94Wa1Wpnw8h3lfL+O6azty38DbWLV2HUPuVzPE69erozmmdq0YZnz8hkfnr1zZ83kCnmjVsjkA638xcdMNXfO359gC5IgIdTe2799DpB05lv99VCjffw/33KMyVRyFhMC776pFGXXeXfNKRhX9S67jwBQQQQfwIvCN2WLabdAH0MqBaWnqccqGDdq2W25RIxzV3U/ikZz94DV77iLmfb2MwYPuYPTj6tn+wUP/sSP5H55+4iG3x1SqFI6+fRtfdjNf29ZXcO01V7Pm+5/p9X/XcV2XjhxOPcpX878FoF7dOuTl5fHp9C95+YVRfumj31itakLoM8+ouRyOataEBQvgppv80zdRpuQ6Dkx+DzoMemNboA+B9kjFbIY77oBDh7RtL74Ir75a6Pop3bt3JzExkbXb19DP2K/Il5Oc/cBw4uRpZsxZQPsrW/HkyCH529u1acHENz7kjltvotlljTXH5eXlcfZspkevoQsJISqyqtf6DPD6K8/wwadf8MY7nxEdFclV7VoSY5vV3vHqK/nfwuX0vPE6KoWH58+Ct6fZnT9/AZ1OR6VK3r1z87tz5+DRR+Hzz7VtbduqUcrmzX3fL1Hm5DoOXH4NOgx6YygwFRhptphyitrfZ776CmJj1ZuWo4gImD1bDdMWQXL2g9MvG7dw/sIFHrj3DkIcyl0fOapGrKoUMHEsNe2o354FA0RHRzHu+cfyv87Ly+OWu2JpecVltLziMt77YCbmbW7mMgDX/t+AMumTX/33H9x5p1pHxdWdd6pAREYVyy25jgOXv0c6ngaSzBbT9tKe6LFHHycyMlKzfeHiBZ6fJDdXFft66y1tW+PGsGyZqsPhAXvO/vTp04lfEF9g2qzk7AeW4+knAWjd8uIKorm5uaz5fj1dOxu49BL3/z++fBacm5tL+omT1Kldq8B95ny5hOPpJ5k4Lg6dTscLz4zg7FnnRQiXrljLNyu+Z85nbxFeyN3RypWrqJaxgZW/b2HPCec5SsW6vorglWsY1EJtd92lVop19coratG2AtZPEeWDXMdaZvNWft/xD9/t0U4X8OZ1XBS/BR0GvfEKYBDQxV99cHLiBNx3H6xerW3r1g0WLoS6dYt1SqkEGnxa2yZzZWZevLC/+GopVapUJv7l0QUe5+1nwfa0vRzXbCngzXensmxFItM/ep0OV7XWtG/dtoOpM//HM0/Gco2xA4DboeRfN20F4Mp22onQQWv2bPVI5YJLIaWoKJg7Vz0yFeWeXMeByy9Bh0Fv1AHTgSfMFtP5ovb3xCeffUzTpk1LdnByskql+/tvbdtjj8GUKcWqTGgnOfvBp1PH9owaMZhPZ3zJtddczanTGYSGhjDr0zcJL8HvQEn8ZtrG8u9+AC6m+13b+WqaNm4IQO1aNYmOiiQy0rlkfl5eHstWfM+sLxby+ivP8H89rvVKf/r27QMp57n+/v5Qq+wmepfqGs7OhmefhQ8+0LY1a6bmb7RrV6r+ieAh17GWwXA1hs7XMazlk145X0nprK5lvH3AoDeOAlqaLaYn3LStA7oDN5gtpnVFnUun0zUF9u3bt69kb1grVqgRDtdU1fBw+OgjGO55GdvCpKWlSc6+vx1YDMd+gxZxoCtfw+sLlnzHgYP/0aRxA27u2Y3oKO1jihI7ewBSlkFjt0FHqfNMS30NHz8OAwfCjz9q2266SVUPjvEsdV0EuMwU2P0JxHQq0wDYX8r0Ot73BYRXBfdBh3fzxQvhr8crdwPdbcFHQX6ypc8mmS2mHl7vgdWqqoi+9JJ2/ZS6dWHxYlXu3EskZ1+UpYF33VL0TuXR77+rRyb79mnbnnpKzc8qRilqIfypIlzH/roaDwC7CmhrDEQAB4FM277edfasWlth4UJt29VXqwmjjRp5/WWFEF60eDE8+KBagNFR5cqqmN+QIe6PE0L4jV+CDrPF9GBBbQ6PVx705PFKse3fr+6MtrtJmLnvPpgxQ6XGCiECU16eykJ59VVt26WXqnVVOnXyebeEEEWrWOOOSUmqwuixY87bdTqYPFlNRPNyKWQhhBedPg2DB8O332rbOndWC7Zdconv+yWE8Ej5mk1XEKsVPv5YTSpzDTiqV4fvvoPnnpOAQ4hA9s8/0KWL+4Bj2DBYt04CDiECXPkf6Th/HkaNUo9NXLVqpVLpWrTwfb+EEJ5bu1ZVAj550nl7aCi8/766xuWmQYiAF3BBh1czVVJToX9/+PVXbdutt8KXX0K1al57OSG84e89+/n8yyU0bngpB1MO06jBJcQOGUBoIWv9AHyz4nu2/5FMtWpRHE49SrOmjXh46MD843Jzc5k1dxHLlidy4uQpmjRqwLDBd9Pr/7yXpeV1Viu89x48/7x2wbZatdSCbTfe6J++CVEIuY7dC7igw2u2bFETRlNStG3jxkF8vJRCFgHnn73/8vDjY/l0ykTatLoCq9XKk8/G807CDMY8PaLA4774ainrf9nM9I9eR6fT5R83fc58Ho29D4Cps75mR/Ju+t/em9S0o6xY9RMvTnib0NAQrxUg8qqsLFUnZ948bduVV6pRyssu82mX0tLSmDFjBklJSVJvRxRIruOClc9P3XnzVI0N14CjalV1Z/TaaxJwiID09pTptGrRjDatrgBAp9Px4P13snDpKnb9vbfA41au+Yl2bVqgsz1i0Ol0XH9tR9at3wRA+omTpKYe4eP3JvLQgwMY+9xjfPTeK+h0OuZ9vazMv69iO3RILT/gLuCwj176MODIyspi+PDhNGrUiJdeeonExER+++03EhMTGTduHI0aNWLEiBGcc10kUlRIch0XrHx98ubmqgmhgweruRyOmjRRb1QDBvinb0IU4b/DaWzZ+geGDs7lutu3a01oaCjfrPi+wGPDw8IwW5xXnzx+4iQxMTUA2P7HTkY+cr9T+9Ud2tK44SUcTj3qnW/AW379FTp2VKOVrl59VdXXiYryWXeysrLo06cP06dPJzs7mzYN2xDXdzQT740nru9oWjdsTXZ2NtOmTePmm28mKyur6JOKckuu48KVn8crp07BiBFqwpmrHj3UCEedOj7vlij/rFZr/sJORdGFhBBRwLLaf/6l1v5p1NA5A6NSpXDq1a2NZftfBZ6378038E7CDF5/+xOee2o4aWnHSPzxF14b/xQAN3Tr7Pa4yMiq1K4dQCXCZ8xQ6x1lZztvj4pSox633+7zLsXFxZGUlERk5Ui3q0X3M/bLXy06KSmJ0aNHM3XqVJ/3U5SOXMe+UX6Cjttvh3//1W4fNUpNRPPRIj+i/Eje+Q9Lvl3LJtM2Jr82hmPHT/DGO59wx629GP7Qvfn7HU49Qr8Bnq3Rc0n9uqxYNN1t25GjxwGoXj1a01ajejT7D7iZn2QzaEA//tn7L4u/WcO2P3ZSr04tPnl/IvXrFRxo5+TkcvDQYZ6Je9ijvpe58ePVSrCuLr9cVQlu29bnXUpNTWXOnDkAbgMOO0PzjowfOJ4xc8cwe/Zs4uPjZY5HgJDrOLCUn6DDNeAID4dPPoGHg+M/QgSe1q0up/XuvXz/0y9kZmZx5Mgx2rS6QrMqZO1aMcz4+A2Pzlm5csHB7wXbcuzh4drLslKlcM6fv6DZ7uiFp0ew46+/2bPvAPv/PcS6nzdx7923Frj/z7+aaNK4AX179/Co72XOXcDRqxd8/TXUrOn7/gAzZ84kOzub1g1bFxhw2Bmad6RVg9bsTElm5syZss5SgJDrOLCUn6DDUb16qjLhtYE/k1cEtp2799C29RVs/yOZhx4cQP87btbsU6lSOPr2bUr9WjWqq/TtnJxcTVtOTi41axSc3n02M5Onxkwi7vGhRFSpwkvx7/H2FHUn5u4N6/z5C8z93zLejH+OkECdVP3ss2pRRj8u2JaUlARAr/a9Pdq/d4fe7ExJZt26dRJ0BBC5jgNHcPSyOOwT0CTgEF7w2yYLKf+lcdftBX/o5OXlkZFxxqM/Z85mFnie2rXU3fzp0xmatlOnMqhbp1aBx05+dyqNGl5Cl056OlzVmnkz3+Wypg35ZPqXbp9Tvz1lOk+NGsYl9esW9u37R+XKatTj7bf9vkJsRob6v4iJ9ux5eUxUTafjRGCQ6zhwlK+RjgcegGnTZME24RX7/j1EyuE0Yh8ckH/34k5q2lGvPAvWt29DWFgYBw+lOm3Pzskh9chRenS7psDzrvt5E08+dnFV1RrVq/Hko0N46oVJ7P/3EK1bXZ7fNn3OfG66sStXtm3pUZ99qkEDNX+jY+GPMnwlOlo9l0/PSPdo//QzJ5yOE/4n13FgKT9Bx7hxKp1OSiELL/n1NzOhoSEMuOuWQvfz1rPg6OgorjG2Z+v2HU7b//hzFxcuZNP7pm6AqkiYfuIkdWpfvGOKiork5EnnO6sGl9YHoGbN6vnbFixeSdPGDels7OC07/oNm+l2nZ9XZr36ali5EurX928/HHTv3p3ExETWbl9DP2O/Ivdfs20NAD169CjjnglPyXUcWMpP0PHwwxJwCK/65betXN2hHXWKSEXz1rNggJEP38/Dj79I8s5/aN3qcqxWK59/tYRe/3cdrVo0A+DNd6eybEUi0z96nQ5XtQZgwJ19WLo8kXvu7kt0VCQASb9spmsXQ/7M99WJ6/n2ux/ocX1nZsxZkP+a/x5MyT+3X331VUAFHACxsbFMnDiR5EPJmPdsKXQyqXnPFnamJBMeHk5sbKwPeykKI9dxYCk/QYcQXpR17jyW7Tt46vFhPn3d1i2b88n7E5nx+QKaNmnI0aPHubxZEx59+L78fWrXqkl0VKTT7PuhD/QnKiqSF8a/RaMGl6DT6ahSpTJvTHwWANPW35kwKYGcnBySd+1xes2wsDCeHvWQb77BwlR2X/fAn+rXr8/QoUOZPn068QviC0ybtdfpABg2bJikywYIuY4Dj85qtfq7D6Wi0+maAvv27dtH06ZN/dwbEdAOLIZjv0GLONCVvznUZebsAUhZBo37Qy2ja2uphxcD/Rq2VyS1Z7K0btiaXu17ExNVk/QzJ1izbQ07U5IB9Thm9erVVKlSxZ9dLr8yU2D3JxDTyd3voijMvi8gvCq0fNJdq88eE8hIhxBCFCIiIoJVq1YxevRoZs+eTfKhZJIPJTvtEx4ezrBhw0hISJCAQ4hCSNAhhBBFiIiIYOrUqcTHxzNz5kzWrVsnq8wKUQISdIiKQxcC6MCaK49XisOaC+jkZwbUq1ePsWPHSuEvf7H/Dlq1hbdEUfIIhNJc/u+BEL4SGgHoIFsKNxVLTobKDAut6u+eiIoutKr6Xcw57e+eBBdrHuRkQpj/r2EJOkTFEdUMQkLhzD/+7klwyfgHQsIhsqm/eyIquvBqUKUunNkPQZ4E4VOZB8Gao94D/UyCDlFxRDWH8Cg4uQ2yT/m7N8Hh7H7IOgjRV0CYVPoVfqbTQfW2kHcOTpj93ZvgkHcBjm+EkDD1s/OzoA862rRqt9bffRAlM6D/QAb0H+i7FwwJhUtvUUONBxZAulkFH3LH5MyaB+eOwNGfIeVbCK8O9f9Ps9uA/gMx6I073JyhWOQaDm4+v45rXQNVG8LRDXB4jUrpzsvx3esHA6sVcrLg1J9wcCGcPw51ukKVOppdvXUde0omkoqKpWYH9fehFSr6P/qz+lomSV5kn2irC1NvUk0GQcQl/u6VEEp4FDQbCvu/hLN7IGOX7Xc21N89CyBWFXjoQiG0EtTrDvV7+rtTgAQdoiKq2UENM2b8o/7kZqq7e6GEhEFYNajeCqo2koBMBJ7wKLh8OJw/Cqf+UnfyeRf83asAooPQKhDZGKq1CogJpHYSdIiKKSQcqrdWf4QQwUenU5NKqwTPsu6iHMzpEEIIIURwkKBDCCGEED4R9I9X7AvWHTp0yM89EcV19uxZAPbv3+/fjogSOXv2LOfOnQvX6XRhVqu1xOkDcg0HN7mOg5u3rmNPlYdVZq8DfvZ3P4SowC6zWq37S3qwXMNCBIRSXceeKg9BR2XACBwGpCC/EL53qDR3SHINCxEQSnUdeyrogw4hhBBCBAeZSCqEEEIIn5CgQwghhBA+IUGHEEIIIXxCgg4hhBBC+IQEHUIIIYTwCQk6hBBCCOETEnQIIYQQwick6BBCCCGET0jQIYQQQgifkKBDCCGEED4hQYcQQgghfEKCDiGEEEL4hAQdQgghhPAJCTqEEEII4RNBH3TodLownU7XVKfThfm7L0KI4pNrWIiKI+iDjjat2v0F7Nu3b182YJU/wfNnQP+B1gH9B/q9H/Kn5P9/Br1xB6Uk13Bw/5HrOLj/eOs69lTQBx1CCCGECA4SdAghhBDCJyToEEIIIYRPSNAhhBBCCJ+QoEMIIYQQPiFBhxBCCCF8Qme1Wv3dh1LR6XRNUel2NG3a1M+9EaLC0ZX6BHINC+Fvpb6OPSUjHUIIIYTwCQk6hBBCCOETEnQIIYQQwick6BBCCCGET0jQIYQQQgifkKBDCCGEED4hQYcQQgghfEKCDiFEyezZ4+8eCCFKIzsbnn7apy8Z5tNXEyKApKWlMWPGDJKSksjIyCA6OpoePXoQGxtLvXr1/N29wJaYCPfcA+np/u6JEKIkjh2DgQPhp5/gvfd89rJSkVRUOFlZWcTFxTFnzhyys7M17eHh4QwbNoyEhASqVKnihx4GMKsVpkyBZ5+FvDywWqUiqRDBZvt2uOMO2L9ffe2F69hTMtIhKpSsrCz69OlDUlISAG0atqFn+17ERMeQnpHO2u1rSD6UzLRp09i1axerVq0iIiLCz70OEFlZMGIEzJ3r754IIUpq4UIYOhQyM/3y8hJ0iAolLi6OpKQkIitHMn7geAzNOzq19zP2w7xnC/EL4klKSmL06NFMnTrVT70NICkpcOedYDL5uydCiJLIy4MJE+C11/zaDXm8IiqM1NRUGjduTHZ2NpMHT9YEHI7Me7YwZu4YwsPDOXjwYMWe4/Hrr9C/P6Smatvk8YoQAaHQOWoREfDAA7B8ufbALl3g11/l8YoQ3jZz5kyys7Np3bB1oQEHgKF5R1o1aM3OlGRmzpzJ2LFjfdTLADNzJowcqWa5O4qKgnnz/NMnIUS+wuaoJSYmMm/CBL6PiuLSkye1B8fGwscf+6ajNhJ0iArDPo+jV/veHu3fu0NvdqYks27duooXdNhT6T76SNvWvDl88w20bev7fgkh8hU1R+3spsW8dewgNV0DjtBQSEiAxx4Dnc8GOQAJOoq0fv3PPBVXvDzmkY89yqeffObx/hEREWz4dT3vvzeFeXO/9Pi45s2bsWDR/GL1rSLLyMgAICY6xqP9Y6JqOh1XYRw9qlLp1q3TtvXsCV9/DTGe/QwDQUmu4YH3DGDB/IUe7fvA4Pt56unRhe7z3rvvs2D+QrfZUgCXXHIJK777tlh9FKLAOWpWK41/XcDlx1PQhBS1a6vJpD16+Li3igQdRejY0cDX87/ixMmT/PH7H8yeNYesrCynfWrVrsWQIQ/SqlVLqlWvTp06tbm+23UcP57OFtMW5s39ktzcXKdjGjduzAOD76f55c2pFh0NwINDBtPnlj4cOXKEn9f/zJLFSzX9adOmNQPvGUjTpk2oUaNGmX3f5VG07eecnuFZbYn0MyecjqsQtm1TqXT//qtte+YZePNNCAuut42SXMPVq1ejy7VdWLRwMb9s+EVzzqaXNeXZ557hkkvqU6tW7SL78PQzTxE3+km2Wbbx7DPPc/r0aQAiIyMZOmwIXa7t4p1vVlQYqampzJkzB8Ap4AjJPk/rb9+l/h8/aI7ZDlz63XfUMRp92FNnwfXu4QdVq1blihZXANCpk5Fz584xa+Zsp31eHPsCN9zQw2mbPSC49toupKWlsXrVGqf2N996nZYtWzptq1WrFrVq1aJVq5Z063Y9e/7Zw/btv+e3h4WF8cGHCdSMqemV762i6d69O4mJiazdvoZ+xn5F7r9mm/o/6+GnOwKfW7AAhg3TptJVrgwzZqiJaEGopNdw3bp16dbtel4Y8yKJa793aut67bV06dK5WP0IDQ3F0NHANZ07kbj2e0JCQnhvyrt07Ggo7rckhNs5apVPHeGqrydQ7fBuzf6rIqK5OyuDcYmJjPVj0CFl0IupdZvWmm16fYdCj2nTpo3T11WrVtUEHJ68VpOmTSTgKIXY2FjCw8NJPpSMec+WQvc179nCzpRkwsPDiY2N9VEP/SQvD8aNUxVGXQOOBg3g55+DNuBwp7jX8JgxzxMZFem07bdNm0r8+sePHQeg7623SMAhSsx1jlr1f/+g07SRmoDDio5//i+WNTc8RCawzt1jUx+SoKOYoqKiNNuqVatWrGOiq3k2XO96XLXowl9HFK5+/foMHToUgPgF8QUGHvY6HQDDhg0r3+myp07B7bfD669r2669FrZsAT/eFZWF4l7DNWNq8uCDg5227flnD3/88WexXzsjI4M//9yBTqdj6LAhxT5eCDvHOWqXmldy9efPUunsSad9cipVZfugV/n3+vvy57L5e45amT1eMeiNNwDRZoupXM2OCgnRxmnutjnShThP5QnReRbruZ43JMS3s4zLo4SEBHbv3k1SUhJj5o6hdcPW9Grfm5iomqSfOcGabWvYmZIMqMcxCQkJfu5xGdq9G267DXbt0rY9/LDKXKlc2ff9KmMluYbvHXQP8+Z+6fSG/b+vvubKN4pXaClxbSIXLlygy7WdpSaJKJXo6GjCgRt/XUTrA79r2jNjGrB90Ktk1mkCBM4cNa8HHQa98WrgDaAXMBFwG3QY9MZQ4AlgKNASyAa2Am+bLaaV3u6XEKAyhVatWsXo0aOZPXs2yYeSST6U7LRPhVh7ZdUqGDRIjXQ4CgtTqXQjR/o8lS6QRUVFMfCeAcycMSt/2/fff88TT47ikkvqe3yeRYuWADBgwN1e76OoWPoYDIxLTOQ6NwHHscuN7Oj/EjkRF0f1AmWOmtcerxj0xhoGvfF54D6g0BlWBr1RB8wH3gfaApWBaKA7sMKgNz7hrX4J4SoiIoKpU6dy8OBBJk2aRM+ePencuTM9e/Zk0qRJHDx4kKlTp5bPgMNqhbfegr59tQFH7dpq9Vg/5O4Hg0H3DXL6ncjNyeXLeZ6nuG/ftp1dO3dRv359rrv+urLooqgoLBaenDuX7m6a9ne9h+33TXIKOAJpjpo353ScMltMb5ktpmeBVUXs+wgq2OgBRABRQF9gr639bYPe2MCLfRNCo169eowdO5a1a9eyceNG1q5dy9ixY8vvHI7MTLj/fhgzRgUfjtq3V/M3KkqmTgnUrFmDO+683WnbsqXfcMo1eCvAfFvdj/5330VoaKjX+ycqiPnzoWtXQlNSnDZnh4bxZ/9x7Ok5HEIu/n4F2hw1rz1eMVtMju9i54rYfSTQx2wx7bd9nQN8Z9Ab/wUsqJGPPsAMb/VPiArtwAFVf8Ni0bYNHAizZkFkpLZNOBn84AMsWriYnJwcQFWEnP/1AoaPeKTQ444fP86PP/xIeHi4JnARwiO5ufDSS6pWjouDwB25OWRtWkKvc2cDeo6az+t0GPTGlsBah4Ajn9li2mHQG7cAXYBavu6bEOXSzz+rBduOHnXertPBpEnwwgvyOMVD9evX5+Y+vVmx/OK0s/lfL+DBIYMLfRy3dMkysrOzublPb2KCqJqrCBCnTsF998F332macq+9loRmzfhj/nyyg2COmj9SZveiJpgW5IDtbzclEYUQxfLZZ3DjjdqAo1o1teLkiy9KwFFMQ4cOQefwMzt58iTfflNwkl5OTg5LFtsmkA4cUOb9E+XMrl1wzTVuAw5GjCD0p594Z+7coJmj5vORDrPFlI3KVClIfeA8kFic8z726ONEuhkeXrh4QbH6J0S5cOECPPkkTJ2qbWvRQi3Y1qqVR6ca0H9ggW3evL6C5Rq+rNll9LihOz/9uC5/27y5X9L/7v5u52okrVtPWtoRWrS4gg4d2vuwpyLoffedyjKzlc3PFxYGH34Ijz6av8k+R62gxSl9dR0XJaCKgxn0xspAB+ALs8V03M/dESI4paXB//2f+4CjTx/YtMnjgEO4N+yhoU5fp6T8pymVbrdggZpAOmCgpMkKD1mtau7GrbdqA446deDHH50CjmASaGuv3IUaBXmxuAd+8tnHUmxHCLNZTRg9dEjb9sIL8NpralnrYvDVXVAwXcNt27alUycjmzeb8rd98fkX3Nynt9N+e/fsZYtpC1FRUfS5pY+vuymCUWYmPPSQylJxpdfDsmXQuHGxTxsoI4YBM9Jh0BsjgVeBQTLKIUQJfPUVXHedNuCIiFBtb7xR7IBDFMx1tGPXrt1s3Pib0zb7KEffW/sSERHhq66JYPXvv+oadhdw3HsvbNhQooAjkARM0AF8BLxltpjcj1EKIdzLzYXnn1c1OM65ZKs3aqTeqAYN8k/fyrFO13SibVvnxRw/n/N5/r/Pnj3LdytVySJ5tCKKtH49dOyoTWvX6WDyZHXjULWqf/rmRQERdBj0xpeAv80W0zR/90WIoHLihHru+/bb2rbrr1cFv66+2vf9qiCGuox2mDZv4a8dfwGwYvlKzp49i7FTRy67rKnvOyeCx6efqnlYx445b69eHVasUDcV5STLzO9Bh0FvfBiobraY3CxzKYQoUHKySqVbvVrbNnIkfP891K3r+35VIDfc0IPLLrvMaducOV8AsHDBIgAGDJA0WVGACxdgxAi19ICt4Fy+li1h82a45Rb/9K2M+DXoMOiNAwGj2WJ6roD2W33cJSGCw/LlKuD4+2/n7eHhKmvlk0+gUiX/9K0C0el0DBn6oNO2n378icWLlrBv3z7q1q1L9x7d/NQ7EdDS0lQNnWluBvj79lVZZi1a+L5fZaysgg77jKkCz2/QG/sAdwCPuWmLNOiNL6Nqdggh7KxWVUX09tvBYZl1QI1q/PgjDB/un75VUDf3uZn69S++VeXl5TF58lsA3HnXHYSFBVqSoPC7LVvU/I1fftG2jR2r6uhUr+77fvlAWSxtXwuwL6HY1aA3hpktphyXfa4HFgOVgIEGvdH1NKHAWSToEOKis2dh2DBYuFDbdvXVKpWuUSOfd6uiCw8PY/CDD/D2W+/kb8vNySUsLIw777rTjz0TAenLL+Hhh7WTviMiYPZsuOce//TLR7y5tH2obd2Uf4FLbZtvBP4z6I1LHfZrAaxAjYaEFvAHYL7ZYjrjrf55S15urmZbrpttzsfkOX+dV/j+BZ03Ny+vgD1FubdvH1x7rfuA4777VIaKBBweKck1XJQ77rydmjVrOm3rcUMP6tSpXarzinLEnmX2wAPagKNJE/j113IfcIB3V5nNBTp6sN9uIGjHjU66Wcb65MmT1KpV8Pp0rktfnzx1CqvV6rR+g0fHnTzpeUdF+fHTTzBgABx3KV8TEqJS6Z55ptzMbPeFklzDRalSpQqD7ruXTz7+NH/bQEmTFXYnTqibA3eTvrt3VzcTder4vl9+4PfslWCzbes2zbZNv20q9BiLS971+XPn2bZte6HHWK1WzT4H/j3A4cOpnnVUBD+rVa2v0LOnNuCoXh1WroRnn5WAo5hKcg17YuA9A/LXjmnW7DIMHQ2lPqcoB5KToVMn9wHH449DYmKFCTgg8MqgB5zMzExSDqVw7PhxTJtNLFq8WLPP22+9S2pqGle1v4rq1atTp05t0tLSOHLkKD8n/czP6zdojhn34jgGPziYVq1aUqNGDS5rdhnp6emkpR3h8OHDrF61hn/+/sfpmLy8PJ4c9SSD7h/E5c2bU7NmTRo1liH1cun8eZVGN2uWtq11azXR7IorfN+vIFSSa7hZs8vcLt5WmOjoaO4e0J/P53whxcCEsny5KtrnOuk7PBw+/hgeecQ//fIjndVq9XcfSkWn0zUF9u3bt69M1m1Yv/5nnop7uljHjHzsUT795DOP94+IiGDDr+t5/70pzJv7pcfHNW/ejAWL3JTLFcHt8GHo3x82btS29esH8+appekDQ6mHWQLxGv7+x0Rq1qxR7Nc6duwY9wwYxLcrlrldMVdUEFYrvP46vPyy+rejevVg8WLo2tU/fXPPZ8OlEnQIEUg2b4Y774T//tO2vfQSTJyo5nIEjoAPOoTwqTNnVJbZokXato4dYelSaNjQ9/0qnM+CDnm8IkSg+OILVWPj/Hnn7VWrwuefw90yZC9EQNu3T63y/Pvv2rYHHlCFwCr4wn8BdcskRIWUkwNPPw1DhmgDjqZNVSqdBBxCBLaffgKjURtwhITAO++om4oKHnCAjHQI4V/p6So3/3s3iyvfcAMsWAC1pdaDEAHLaoWPPoKnnlK1OBzVqAFffw29e/ula4FIRjqE8Jc//1R3Ru4CjieegDVrJOAQIpCdP6+qiz75pDbgaN0aTCYJOFzISIcQ/rB0KQwerEqbO6pUSS1z/dBD/umXEMIzhWWZ3XYbzJ0bSFlmAUNGOoTwpbw8lYFy113agKN+fVi3TgIOIQLd5s0qE8VdwPHyy+qmQgIOt2SkQwhfyciABx9UC7O56tQJliyBBg183i0hRDFIllmpyEiHEL6wZw906eI+4BgyBJKSJOAQIpAVlWW2caMEHB6QkQ4hytr338PAgWrRJ0ehoSqVLi5O1k8RIpBJlpnXyEiHEGXFaoX331ez110Djpo11QJQo0dLwCFEICssy+zJJyXLrJhkpEOIsnDuHIwYoZ7/umrXTj1mad7c590SQhRDYVlmn32myp2LYpGRDiG8LSUFunVzH3Dcead69isBhxCBKy8P4uMLzjJLSpKAo4RkpEMIb9q4Ub1RpaZq2yZOVIu2BdaCbUIIRxkZarLo0qXaNskyKzUJOoTwllmzYORIuHDBeXtUlCoUdMcdfumWEMJDe/fC7bereRyuhgxRj1SqVPF9v8oRueUSorSys1XZ8thYbcDRvDn89psEHEIEuu+/VxNGXQOOkBA1IXz2bAk4vEBGOoQojWPHYMAAVUnUVc+earGnmBifd0sI4SGrFRIS4Jln1FwORzVrqnTYm27yT9/KIRnpEKKktm9XpZDdBRxPPw3ffScBhxCB7Nw5NSH0qae0AUfbtmrBNgk4vEpGOoQoiYULYehQyMx03l65MkyfrtLshBCB67//VDbZ5s3atjvvVCXNo6N9369yTkY6hCiOvDyVgTJwoDbgaNAAfv5ZAg4hAt1vv6lRSncBx8SJsGiRBBxlREY6hPDUqVPwwAOwYoW2rUsXlUpXv77v+yWE8Nzs2fDoo5Jl5icy0iGEJ3bvhs6d3QccsbHw008ScAgRyLKz1TpHDz2kDTiaNVM1diTgKHMy0iFEUVavhnvvVSMdjkJD1az3xx6T9VOECGTHj6tHoj/+qG276SaYP18mffuIjHQIURCrFd56C265RRtw1K6t8voff1wCDiEC2e+/q/ob7gKOp56CVask4PAhGekQwp3MTHj4Yfjf/7Rt7durBduaNvV1r4QQxbF4MTz4oPsss2nTVJvwKRnpEMLVgQNw/fXuA44BA+CXXyTgECKQ5eXB+PFw993agOPSS2H9egk4/ERGOoRw9PPP6o3qyBHn7TodTJoEL7wgj1OECGSnT6u09W+/1bZ17qyyzC65xPf9EoCMdAhx0dSpcOON2oAjOlq9gb34ogQcQgSyf/5R6evuAo6HHlLVgyXg8CsJOoS4cEGtDvvoo5CT49x2xRWwaRPceqt/+iaE8MyaNWrC6F9/OW8PDYUPP4QZM9RcDuFX8nhFVGxHjkD//rBhg7bt5pvVvI4aNXzeLSGEh6xWeO89eP557foptWqpJQtuuME/fRMaMtIhKq6tW1UpZHcBx5gxqhCYBBxCBK6sLDUh9NlntQHHVVepBdsk4AgoMtIhKqb//U894z13znl7lSowaxYMGuSffgkhPHPokKogajZr2+6+W5U7j4ryebdE4WSkQ1QsublqFOO++7QBR6NGKh1WAg4hAtsvv6hRSncBx2uvwYIFEnAEKBnpEBXHyZMqoFi9Wtt2/fVqZcm6dX3eLSFEMUyfrioBZ2c7b4+Ohnnz4Lbb/NMv4REZ6RAVQ3IydOrkPuB49FFV0lwCDiECV3Y2jBoFw4drA47LL1dZZhJwBDwZ6RDl34oV6nFKRobz9rAw+OgjGDHCP/0SQnjm6FFVDTgpSdvWu7eao1Wzpu/7JYpNRjpE+WW1wuuvq7sf14CjTh21AJQEHEIEtm3b1PwNdwHHc8/BypUScAQRGekQ5dPZszBsmMrRd3X11bB0KTRu7PHp0tLSmDFjBklJSWRkZBAdHU2PHj2IjY2lXr16Xuy4EN4T9L+3CxbA0KEqNdZRlSqq2Nf99/ulW6IUrFZrUP8BmgLWffv2WYWwWq1W6759Vmv79larGutw/nPffVbr2bMenyozM9P6yCOPWMPDw62A5k94eLh1+PDh1qysrDL7dgKcXMMBKOh/b3NyrNYXX3R/DTdsaLVu2eLvHpY3PvvMlpEOUb6sW6dy9I8fd96u08HkyaqIkIfrp2RlZdGnTx+SbMO6bRq2oWf7XsREx5Cekc7a7WtIPpTMtGnT2LVrF6tWrSIiIsLL35AQxRP0v7enTqkRjJUrtW1du6rl6oNhlEa4pbOqO42gpdPpmgL79u3bR1NZbrzislrh449h9GhVi8NR9erw9deqrHkxDB8+nOnTpxNZOZLxA8djaN5Rs495zxbiF8Rz9vxZhg8fztSpU0vxTQSlUq+AJ9ewdwX17+2uXXD77epvV488oiZ+V6rk+36Vfz5byVKCDhH8zp9XefszZ2rbWrWCb76BFi2KdcrU1FQaN25MdnY2kwdPdvvGbWfes4Uxc8cQHh7OwYMHg+NZufdI0BFAgvr3dtUqVUfn1Cnn7WFh8MEHKrVdVnkuKz77wUr2ighuhw+rtRXcBRy33qpy94sZcADMnDmT7OxsWjdsXegbN4CheUdaNWhNdnY2M931QwgfCcrfW6sV3noL+vbVBhy1a8MPP6hVoCXgKBck6BDBy2RSS1lv3KhtGzdOjXBUq1aiU9ufh/dq39uj/Xt3UPutW7euRK8nhDe4/t6eOJPOl+u/ZMwXz/PEjFGM+eJ5vlr/JSfOpAMB8Hubmanmb4wZo4IPRx06wJYt0K2bX7omyoZMJBXB6YsvVGXC8+edt1etCnPmqEJCpZBhq+sREx3j0f4xUTWdjhPCH+y/f9ER0bz37Xus3baGnLwcp33Me818se4Leut7o79M73ScTx04oBZss1i0bffcoxZerFrV590SZUuCDhFccnLUXdF772nbmjRRoxvt25f6ZaKjowFIz0j3aP/0MyecjhPCH+y/f7N/nEVKegpQcPbKSvNKtu3b5nScz/z8M/TvryqNOtLpVEG/MWPkcUo5JUGHCB7p6XDvvZCYqG3r0UMVAqtd2ysv1b17dxITE1m7fQ39jP2K3H/NtjW2bvTwyusLURL239uU9BSqVo5kgpvslX7Gfpj3bGHigvj8wMSnv7effQZPPKFuIBxVqwZffaXmdohyS+Z0iOCwY4eav+Eu4HjiCVi71msBB0BsbCzh4eEkH0rGvGdLofua92xhZ0oy4eHhxMbGeq0PQhRXv34XA2R3AYedoXlHJgwcn//1bb5YKO3CBZWBMnKkNuBo0QI2b5aAowKQoEMEvmXLoHNn2LvXeXulSipr5YMPIDzcqy9Zv359hg4dCkD8gvgCAw97vQOAYcOG+T/tUFRoy5cvByhW9grAt99+W7YdS0uD//s/cFcP5JZbVJZZy5Zl2wcREOTxighceXnw2mswYYK2rX59WLIEunRx2uzNtSYSEhLYvXs3SUlJjJk7htYNW9OrfW9iomqSfuYEa7atYWdKMqCGtRMSEkr8rQrhDSXJutqZksy6desYO3Zs2XRq61Y1YfTgQW3biy/Cq69CaGjZvLYIOBJ0iMCUkQFDhqiF2VwZjWp7gwb5m7KysoiLi2POnDlkZ2c77Z6YmMgrr7zCsGHDSEhIoEqVKh51ISIiglWrVjF69Ghmz55N8qFkkg8lO+0THh5e7PMKUVYCLuvqf/+Dhx6Cc+ect0dEqOyUe+8tm9cVAcvvQYdBb7wLGAFEA+G2v78F4s0W0xl/9k34yd69qhTyn39q2x58UA3ROnzAl+VaExEREUydOpX4+HhmzpzJunXrgnO1TlEhBEzWVW4ujB2rin65atxYPTLV6737miIo+DXoMOiNHwD3A73MFpPZtq0ZsBq4yaA3djVbTFmFnUOUM99/r3L0013eNENC4N13IS5Ok0oXFxdHUlJSgWtN2Gfrxy+IJykpidGjRxd7rYl69eoxduzYshuCFsILAiLr6uRJVc589Wpt2/XXw6JFULeu915PBBW/rb1i0Bu7AL+iRjQmuLQNABYAcWaL6YPCziPrNpQTViskJMAzz6i5HI5q1oQFC+CmmzSHBfVaE+WDrL0SQFyvh2b1mvHd1lX8vn87mRcyqVqpKu2btqfP1X3Ym7bX+9dDcrIapfz7b23byJEwZYos2BaYfFYUxZ8jHdfb/nY3DmgfV2/to74Ifzp3TqXSff65tq1tW1Xwq3lzt4eWZK2JnSnJzJw5U0YtRLljz7qaPn06474chxUruXnOqy6b95r5fN3n6GyfM17LulqxAu67T83HchQerlaHHT689K8hgp4/U2btv5l93LQ1tP29z0d9Ef6SkgLdu7sPOO68EzZuJC0qikmTJtGrVy+6dOlCr169eP3110lLS5M1UoRw8eabb1K9enVy8nLIzculTcM2xPUdzcR744nrO5rWDVuTm5dLTl4O1atX58033yzdC1qtqorobbdpA466deHHHyXgEPn8OdKxGsgFehv0xjizxZQAYNAbdcBo4AggS3aWZxs3wl13QWqqtu2VV8h69lninnqq0IyUmjXV7PuAma0vhJ+98MILnDp1iqqVqzJh4IRCKpJO5NSpU7zwwgvFnuOU7+xZGDZMVQN2dfXVasJoo0YlO7col/w20mG2mPYBr9i+nGLQG6ca9MZLgM+BWkBXs8V03F/9E2Vs1ixVutw14IiKgqVLyXr+efr07cv06dPJzs52e7eWnZ3NkSNHgACYrS9EAEhNTWXOnDkAbgMOO1WRVE2lmz17NmlpacV/sf37oWtX9wHHfffBhg0ScAgNv2avmC2m1wx6YxgwARgOPAzMB641W0x5hR7s4rFHHycyMlKzfeHiBd7oqvCW7Gw1WfTDD7VtzZqp+Rvt2hE3fLhHGSkvffUS2bnZskZKGRrQf2CBbd68vuQaLj2fzXFat06t5HzsmPN2nQ4mT4Znn5UF2wKMr67jogRCGfSJwHLbv0OAQcCHBr3Ru3Wthf8dOwa9e7sPOG66CUwmaNfO6W7NXcBhZ2jekTF3jgGQNVKEoGQVSaEYc5ysVvj4Y3W9ugYc1avDd9/Bc89JwCEK5O86HZHAPCAbuAr4BLgOeAy4zKA33m62mLILOUW+Tz77WNLtAtn27aoU8v792rannlJFhMLUr2Nx7tZ6tLuBD7/7iFOZJ5m4YGKBQ8qyRkrJ+eouSK7h0ivTiqTnz8Pjj6v1jly1aqVGKVu08LivwrcCZcTQb0GHQW8MAVYAdQCD2WI6b9AbuwPjUKMffYBngTf81UfhJQsXwtChkJnpvL1yZZg2TVUZdVDcu7UHuj3Ax6s/IvN8pqyRIiq0SrYaGMWd41S5cuXCd0xNVZO+N27UtvXrB/PmqaXphSiCP0c67gJ6AE+YLabzALZ5HK8a9MY84DUgDgk6gldenlqs7bXXNE0Z0dGMbd2aLZ9+SvS8eU4lxYt7t1a3eh31d926nDhxQtZIERWWPego7hynSoUV7DKZVPp6Soq27aWXYOJEVTFYCA/4M+joavvbTek63gaeAuoZ9MYYs8XkWdguAsfp0/DAA7B8uaZpo07HXRkZpG7enL/NcVE2+2TC4t6ttW/fnrlz58oaKaLCunDhAnBxjlNRFXrtI4Dnz593v9PcufDII+rRiqOqVWHOHDWZVIhi8GfQYV/LWFOE32wxXTDojXtRqbM5Pu2VKL2//1alkJOTNU0zgMetVi5v2IZ7CliUzf5cvyQZKbJGiqjI7EEHwMQF8UwoYCK2qtMR7/Y4AHJy4IUX1HpHrpo0UfM32rf3Wr9FxeHv4mBPADcDcx0bDHpjJaAZ8KvZYjrth76Jklq9Wi32dPKk0+ZcnY44q5U5lary6j0FFyyKXxDP/v37CQkJKdbdmmSkCHGx/kyDmAakpKcUOcfJvp9T3Zr0dLXkfGKi9gV69FBztGrX9sF3I8ojfxYH+w5VCGyQQW8cZatEikFvrAx8iBoJecxf/RPFZLXC229D376agCOvZk1uDgnhY2C8m4DDztC8I+MHjredTi1EGL8gvsBUWMlIEcJZ9+7dAYiKiKKvoS9hIWEkH0omYeUUJsyfQMLKKexMSSYsJIy+hr5EVokCHOrW7NgBnTq5DzieeALWrpWAQ5SK31aZtTPojYOBEcClwH9AFWAL8LrZYjpQ1PGyQmUAyMqChx+Gr77Stl11FR/17MkT775L64at+fDhj4o83ajpo9iZksxll13Gvn1q+Z2iMlJWr14tE0T9Q1aZDSDuVpldtXUV2z1ZZfa339Q8rDNnnE8aHg6ffgoyklie+aywit+DjtKSNyw/O3hQ1d/YulXTlNyuHTHffMPgRx8lMTGRuL6jPZqjsdy0nISVU7jxxhu5/PLLmT17tmbtFZCMlAAhQUeAGT58ONOnTy+wmi9cHCU8e/4sIx55hM8aNlSZZq7q1YMlS+Daa33Qc+FHFWJpexHsNmzA2r8/Otv6J3Z5wEvAG3/+SXirViVelC0zM5OpU6cSHx8vGSlCeCghIYHdu3eTlJTEmLljqFOtDhGVIsiz5hGiCyHzQhbHTh8F4ObrruPjI0dg+nTtiYxGFXA0bKhtE6KEJOgQJTNtGtZRo9C5jECcC6vEsi53k1mtLq1tGSn2RdmOnDzi7kwarouySUaKEJ6LiIhgyZIldO3alZ07d3LUFmC4uqlZM1akpxO6YYO2cfBgVbhPRhCFl0nQIYrnwgWIi4PPPtOMx2XGNGD7oFepU6cJ/XBeQjvzfCZf/jyPOzvfWeRLyKJsQpRcVlYWd911Fzt37gSgTcM29HRJT7/kUDJf792bX7cgX0gIvPMOjB4t66eIMiFBh/DckSNw993w88+apmOXG9nR/yVyIqKcttuX0B4zdwwnz55k3Z8/0aPdDQW+hKTAClE6cXFx+Ss0P9XvKVLS/2ND8s9qIml4BC9FVOMenY5Q1/l8NWvC/PnQs6d/Oi4qBAk6hGe2blUTRg8e1DTt73oPe/4vFkI0902A8xLak5dOJjoiWhZlE6IMOK7Q3LZRW95c8iY5eaq+YmXgU+A+N8fltGhB2MqVcPnlvuqqqKAk6BAFSktLY8aMGejmz+fpHTuokpfn1J4FLOxwMw16Di/yXL079GZnSjLZudmyKJsQZcS+QnPVSlXZ/I9aZqBNwzb0b3ktw7etpuHxQ5pjlgJ77r2XZyXgED4gQYfQyMrKIi4uji9mz+aVnBxecLNPSkgIt+XlcXura2ngwTntGSmyKJsQZce+QnPmhUyqVo5kwsDx3FA5kqu+nkDlM8c1+78CxAM3bdzIsz7tqaioJOgQTrKysujTpw/bkpJYAtziZp+fgbvz8jgCXC+LsgkRMI4fvxhYTBg4nltPH6PVipcIyXXOMssJr8LyawcwMWmu5jghypIEHcJJXFwcqUlJbNbpaOGmcNwhw61satmFE/NfgdxsWZRNiABy6tQpANo1aMW9uzfReNMSzT5ZNS5h+6B4qtVrRqt/1MTt06dliSvhG35be0UEntTUVI7MmsUm0AQceSGh7Ow7ml39nkLfojNj7hwDXFxCuzCSkSKE78QAi86ddRtwpF92NZuHf8zZes0ANddKCF+SoEMoVivJgwezJDeX6i5NF6rWwDLkHVIcRjR6tLuB6lVrADBxwURZlE2IAGCoXBkT0PK4NsvsQOf+bHvgTXKqXrzC7XOtqld3veqFKBvyeKWCsWekJCUl5c+n6HnttTxhsXDD999r9j99yRX8fs9EztfQBgsPdHuAj1d/ROb5TMlIEcLflixhzq5dRLhszgsNZ+etozmsv1lziH2uVUyMZ0sUCFFaEnRUEPaMlDlz5jgtntYEeCsxEXe5IqntbiT5tmfIq+Q+k6Ru9Trqb8lIEcJ/8vJg4kSIj9cEHOejavH7vRM53bC120Ol+q/wNQk6KgB7Roo9nc5eFlmfdYr+G74m6kKW0/55wJ6bHuFA13sKLYUsGSlC+FlGhlon5ZtvNE3/1W7Engff4UK12m4Ptc+1ArjtttvKtJtC2EnQUQE4lkUeP3A8hmYGGpq+4Yp1XxCSl+u070ngkcqRPHrdvUWeVzJShPCjf/5RVYJ37NA0zQaeOX2cF47ux+Am6FBrIsXnf/3tt9/Srl27MuysEIoEHeWcY1nk8QPH07HJVbRc/h4Ntn6n2fd4tTp0OX2Uv8+fpVV5XyMl9zyc3gVn9kJuJlhziz6motCFQXg1qNYKIpsWWN5e+NHatXDPPXDypNPmXJ2Op6xWltS8lBMn/ityrlWDmAakpKewbt264LthsFoh6z84nQznj0PeBX/3KIDoILQKVG0M1VtDeLS/O5RPgo5yzl4WuXXD1nSp24wrP3+WGge1d0bHrriGP/uPJXTuC1De10g5vgX++w5yz0FeDuhCQCcfrPmsOeoN/eivUKk6NL0Pqjb0d68EqP+X99+H555TczkcxcQQV68eHycn89L/xWLZt5U1ljVu51qFhYTRW98b/WV6Xlv0GhkZGT78Jrwg+zTsmwuZ/138fQ0J93evAkie7b3NDCkroHZnuLRPQKwcLEFHOWefxxHbpD3GaSOpknFMs8++6+9j7w1DISS0/K+Rkm6GQ8sgpDLUvh6iL4ewSH/3KrBYrXDhBGTsghNbYO/n0GwoVPWk4L0oM1lZMGIEzJ2rbbvySli2jN2PPgrJyWRkZfBUv6cZesNQVm1dxfb921Vp9EpVad+0PX2u7kPNqBiWm5YDEB0dOHfCRcrOgD2zITMFqreD6m2gyiUB8YEaUHLPw9l9cMICRzeo0dwGt/r95yRBRzngLg3WPokzIyODB4C4jYsIs602aZcbXoW/bn+OI+165G8r12uk5OXAf6tBVwkaDQyoIceAotNB5Rio3EWNcBxaCqk/QLMH/d2ziislBe68E0wmbVv//jBnDkRF0b17dxITE/MrBdeMiuG+bvdzX7f73Z42KLNXjm+CrMNQtzvU1Pu7N4ErtLJ6RBrVHA4tUT+32tdAlbp+7ZYEHUGsoDRYgMTERF6dMIH3q1ThUVAfuI7HVq/H7/fGc+YS55Uly3VGypk9kHMWYq6RgMNTVRupP2f2QE4mhFX1d48qnl9/VYFFaqq2LT4exo2DEFXnMTY2lokTJ+ZXCnb3eNQuKOdlWa1w8k81X6FGB3/3JjiEhEOtLpCyDE7tkKBDlExBabAx0TGkZ6SzyfIdE//bTa8zZzTHnmjanj8GjCc7soamrVxnpJzZB3m5EN3c3z0JLlGXQ1YKnP1XTUoTvjNzJowcCS43FURFwbx5cPvtTpvr16/P0KFDmT59OvEL4lW2Wnmal5V9Cs4fg6gr/P6YIKhUbagmiJ/ZB/UKThDwBQk6gpQmDdbhjSXyyH5e/3UB7u5JD3a6g797j8Qaqv2vD8o7n+LIzQKsECajHMUSFgXWPJXlI3wjOxuefho++kjb1ry5qsvRtq3bQxMSEti9ezdJSUnlb15WbpYa7ZBruHh0IWqUMsf/17AEHUHINQ3WMeCovfMX2i55gzCXgl8XgLiwSlzWsguGAgKOoLzzKQ5rHmCVTJXisv+8rHmF7ye84+hRGDgQ1q3TtvXsCV9/DYWULY+IiGDVqlWMHj2a2bNnl695WfbfQbmGSyAEVfrRvyToCEKOabD5AUdeHpetn0ezdZ9r9j8aEsrteblszLkA5e3OR4jyZPt29cjk33+1bc88A2++CWFFv21HREQwdepUnnjiCZ566im2bt3KhQsXqFSpEgaDgffee0+KgQm/kKAjABWWjVKvXr38eRy92qtlqUPPZ9Fm2WTqJv+sOdepS1vyUavr2PjjTBo0aMCRI0fK152PEOXFwoUwdChkugyBV64MM2bAAw94fKqiJplfffXVcr0Lv5CgI4AU9UbxyiuvMGzYME6dOgVATHQMVdL/o/3X44k6sk9zvsNX9WRnv6cJ/WczAI0aNcJsNpevjBQhgl1eHowfD5MmadsaNIClS8Fo9Ph0RU0yX7tdFQybNm0au3btYtWqVUREuC4VJ0TZkKAjQBTnjaJmTVVLo9a+bXT65m3Cs5yrCVp1IfzdawQHO/cHnS4/DTY6Orr8ZaSIQh1OPUpk1QiqVYvyd1eEO6dOqRGMFSu0bddeC4sXQ/36xTplYZPMAfoZ++XP4UpKSmL06NFMnTq1NN+FKEPl7RqWoCNAFOeN4sSJE8QBIzYt0fwHZleJ5s8BL5HucHxQFgCqoIY/MQ6z5U+3be9PfoluXQu+4z2bmcktdz3MmTNn87c1bFCfZV9/5rTf33v28/mXS2jc8FIOphymUYNLiB0ygNBQmZznU7t3q/kbO3dq22Jj4eOP1aOVYnCdZN6sXjO+XP8lv7upSDp+4HjGzB3D7Nmz/7+9+w5vqmwfOP5Nd2lLoexdEGhBBEIIQ1lOXPhDFBR8RRQciALyqiDioPqK+8VXRBFEQEUEZA8ZyhBkhDQgQhGRsiqlZZTRlo40vz9OW5omKWmbcRLuz3VxtT3POelTnt7NfZ7zDBISEqSn00UkhssmSYcKlDUbpSTddR2Z+MAr1Jg7gSF2yi/ViuX3gW+RHVO/+JjfT4P1I8dTTpKefpannxhIWNiVN5v002f4ceka9Lq2ZV6/dMV6unZqT53atYqPdda3Q1NiPYNDh48ybMR4Pp88kdbxLbBYLIx8MYEPP5nB2DFPu/6HEvb99BM8/LDS01FSUBBMngzPPluhdSiKBpnHNYhj077NvPrdq+SXWhjQeNjInI1z6K3tTcv6cRz850+++uor6f10AYnhq5OkQwXszkaxI+TCaYZt+pZoO2Vp8Tex//5xmEOvrM5xTUyD9SO/bjXw5ZS3qVWzhtXxb+ctpUsnLeFhju96zWYz6zf8xrT/vUVwsOONrz6YPJ34ls1oHd8CAI1Gw+BH7mf4qNfp2+d24lo0c80PI+yzWODDD2HcONsN22rWVAaTVqJHsujx7KXsS6xKXAk4flS70riSBjHKfjo+ucusCkkMX50kHR5S1oyU0rNR7Kl6fD9tf3iT0EtnbMreBBZcPMPtv/8s02B92KAB99k9/sumbfTtc3uZ1/68cRtHjp3grfc+o3PHdvTq0ZmIKtbLw/1z8hS7Evfy9BMDrY63a9OKwMBAlq5Yz8svPFW5H0I4lp0Nw4bB3Lm2Ze3awZIlEBtbqW9RtFtsytkUqoRG8EYZj2onzk8g5WyK1XWiciSGr06SDjdzZkZK0cDQmCj7C/7UM/1E/IrJBJitr88KCGD2rbfyzsaN5KUcYH+K9bNhmQbrORaLhezsy06dqwkIKPOOp6TTZ86xL+kvPn637LvQXaa9BGgCWPnTBlb+tIHo6CjeHD/K6vnxH/v/AqBRw3pW14aEBFOndk1Me/Y7VSdRAceOKRu2JSbalg0YADNnQkTldzsOCQkp/txewlFEd11H3igc01H6umuVxLBnSNLhRs7OSElLSwPg7MWzVtdrzPm0WPsFjXYstnntv4H3OnXiy7Vr6XfqlEyDdaGvv1nIN/OW8POKb4qfpT7/74nk5+fz+Sdv2b3mZGoaffo7d4dRr25tViyc7tS5GzZvp12beKpFVy3zvPEvDmf8i8M5cuwEc+cvZ9HSNbw84V2mf/oON7SJAyAtXekli462XUK6WnQUR46lOFUnUU5btigbthXGeTGNRpkmO26cy/YRKUoervaoFpTEI75BKw6kJBFazgGraicxrF6SdLiRszNSJsydQJ45r3g7aoDgzPO0WZBAzJHdNq/7W2gE9+Zk8mIf5VyZButaRtMfdNS2Kf5jlZubR+KefTw55CGH19SsEcOMzyY59fqhoY6f15a2YdM2evXo7PT5sY0bMv7F4XTRt+flCe/xxcy5fPbxRAByc3MBCA62DfuQkGBycnKd/j7CSV9+Cc89Z7thW1SU8pjl3ntd+u2K2risR7Ul9W7fmwMpScXX+QuJYfWSpMNNyjMjZez9Y3l74dvF21H3jKhO23mvE55hu5W1oVU3eiRtIUBmo7hFfr6ZPXuTeH74Y8XHtu80cflyDp317R1eFxISjLZda5fW5cKFSxh372PC2BHlvvaWnl25uUcXq6l7RXda+flmm/Pz881Ur1b2nZgoh9xcGDUKvvjCtqxFC2XDtlau37G36E3J0aPa0mIilUe7OTk5Lq+Lt0gMq5skHW7i7IwUgF5tbubTVVM4n5XBnu9fY7TFQkip8RvmwGB+6nw/DxlXYgaGymwUt0j68xBZ2ZetprZ9N38Z1apVJb6l41HhBQUFZGY6t4OjJiCAyAh7ewBb27R1J81iG1G/XsXaWadtw287rowhqFlDeYO5cMF20OD58xepXauGzXFRAWlp8OCD8KvttgTceSd8/z1Uq+aWbx0VpXS7l35U60jJhQP9hcSwuknS4SbOzEgp6dHuj1B7zWe8lm/bPZYRGsFTVWux4Lf5gMxGcafE3fuoVTOGpk0aAsqo89RT6XTWWc+VLy31VLrLnwdv2LSNXt2d75YtLS8vn4YNrqxmqW3XmqCgII6fsO5By8vPJzUtvVxdwMKBxETo2xeOH7ctGztWGcPhxgWcevbsybp166we1ZbFHxcOlBhWN0k63KRoCpoz3ZyBlzN5bu964uyUbQP65WSSmp4ps1E8wGj6g/ZtlW7v1FPpHDmWwsnUdIYO7k/66TPUrBFj9w+Xq58HZ2dfZvvO3Tw9dKDdcrPZzNlzGTbrAZS0bUci9955S/HXUVGRdNa3I3HPPqvz9v7xJ7m5efS+rYdT9RcOzJsHTzyhTI0tKSxMmZ0y0H5bulKfPn2YMGFC8aPasnpZixYOBLjvPvtTPX2RxLC6SdLhJs52c4afOUG7718j4vQxm7Kf6tfnnYYNuSE6mudlNorbmc1mdu9NokG9OmzeamDTlh3oO7TFbDbT/LombNqykwf73mX3Wlc/D96yzUiNGtUcLvTz7kfTWLJiHdOnvENWVjZvTvof9/TuxTNDBxEaGsL8H1cSHBLMwP7Wd7vDhz3CsBGvkHTgEK3im2OxWJg9dxF33NqtzK5nUQazGSZMULadL61RI2XDNp3OI1VZvnx58ecT5yc4nDZbtE5HkWXLlvnFVvcSw+qPYUk63MSZbs6YQwbaLHyb4MuXrAsCA2HyZO4cMYI7XTSVTlzdgYOHwWLh/IWLLF2xjjdeGcnv+w4QGRnBitUbGPO85wbubti0jZ7dHHeV1qxRnajICCIiwqlTuyaxjRrww48r2bo9kevjm9NB24aPJ4232YuhVdx1TP3vRGbMnk9sk4akp5+hebMmPDNskLt/JP+UkQGDBsHq1bZl3bopG7bVru2x6hQ91m0Q04CUsymM/WYsrRq24o52ve0uHFh0nr+sSCoxrH4ai8Xi7TpUikajiQWSk5OTia3kan6ulJqaSuPGjcnLy+O9R9+zvtuwWGj82wKar5+OxmK9FHJBTAwBCxbALbcgXOzYj3B6O7QcBZoAm+I5cxdhMO7l04/e8ELlVCzzGKQsgcYPQA2bzaoqnRWrNYav6sABZcO2gwdty555Bj75BDy86FbXrl3Zvn07Ex58DVNyImtMa2z2XgEICgiit7Y32qZa3l74Nl26dGHbtm0erWuFZKXAwakQ08ne76LEcFmS50BwFYgbaa/UY3e30tPhJnXr1mXIkCFMnz6dhPkJxdNmA/JyiF/2EfX2/mxzzfGYGBrt2gVNm3qhxsK4ex/tbnD9NEbhh1auVHo4LlywPh4UBJ9+qiQdXlD0WPdi9kVe6DOGITcPYXXiavbY2WW2emQMyw3Lra7zdRLD6idJhxt98sknHDx4kE2bNjH2m7HcXLc5s7IvUO98ms25G2vWpEtSkrLpk/C4yzk57Ercy6MP9/V2VYSaWSzK2I1XX1U+L6lWLeVxSvfu3qkbto91q0fGMKjHIwzq8Yjd8/1p9orEsG+w7WMWLhMeHs7q1at56qmn6BkYyPeph2hsJ+FY0rEjXY4dI0wSDq9Z+/MWQkNCaNsm3ttVEWqVmanMQBk/3jbh6NABdu3yasIBMHToUIKDg4tnr5SlaPZKsJ8sNCgx7Bsk6XCz8PBwpnXsyIaAAErPO8kJDSVj9mz6GgyEhYd7pX5Ccd/dt/LLqm8JCXF+eWNxDTl6VBkY+sMPtmUDByoLgTVu7Pl6lVL0WBcgYX6Cw8TD+PcuEgpnrzzuJwsNSgz7Bnm84k65uTB6NHz+ue0onebNCV22jFA3LIUshHChTZuUFUZPn7Y+rtEoj1peesllG7a5QunHumXNXpGFBoWnSdLhLmlp0L8/bN5sW9a7t7IUcuGW9kIIFbJY4PPPlT1U8kvNAImOVmL4LvtrPnhT0WPd0aNH8/XXX5N0IomkE0lW58hCg8JbJOlwB5NJWQr5mO2CX7z0Ekya5NalkIUQlZSbq+wOO93OUtdxcbBsGbRs6fl6OSk8PJxp06aRkJDAV199xcaNG7l48SJRUVH0koUGhRdJ0uFqZS2FPGMGPGJ/FLkQQiVOnYIHHoCtW23L7rkHvvtO6enwAXXq1GH8+PF+sfCX8A8ykNRVzGZ45RVlUFnphKNhQ9iyRRIOIdRu1y7o2NF+wjF+vLIlvY8kHEKokfR0uML588pCQatW2ZbddJMyd1+6MkUF5OXlERwso/E94ttv4ckn4fJl6+NVqsDXX8OAAd6pl/B5EsdXSNJRWWUthfzUU8rqhB5eCln4vvTTZ/hq9gIyzl/g3YSXnbpm8fK1/L73AOFVwjicfJwB/e7mlp5dHZ5/4OBhBj/5Ijs3LXJVtX2T2QzjxsGHH9qWNWkCS5ZA+/aerpXwAxLHtiTpqAyVLoUsfNuWbbvYvGUnPy5dQ8/ujjeMKmnu/OX8unUnUycnoNFoOHoshYGPj+aNV563u911Xn4+CZP+h9lsdnX1fcu5c/Dww7B2rW1Zz56wYIGy0qgQ5SRxbJ+M6agIi0WZgdKnj23CUasW/PyzJByiwrp17chLLzzl9PnnL1xkyrQ59L69B5rC9SKaNG5Ar+5deH/ydHJycm2umfPdIqpXv8bHJuzfD5062U84RoyAdesk4RAVJnFsn+qSDp1W31mn1Zt1Wn0vb9fFrrKWQtZqlYFoPWwzUiHKIzjI+U7I37YnkpOTS4P61uOG2t8QT0bGBbZuN1odP3T4KJmZ2bS9/hpeLnrZMujSBQ4dsj4eHKxMk50yRflciEqQOLalqqRDp9WHADNRWb2KlbUU8sMPKzNUVLAUsvA8i8VCVla2U/+yL+e49HufPJUOQEipN8k6dZS9fPYfuPLGajabmTHrB558/CGX1sFnWCzw9tvKOKyLF63L6tSBDRtg2DDv1E14ncSx+6ltTMcbQAtvV8KuspZCnjQJXn5ZVUshi8pL3L2PufOXsS/pL9JPn8VS2LN1XdPGzP/mU6tzT6am0ae/c12p9erWZsVCO4tOVVB0VCQA6afPWh0PL9zPJyPjyiPAb+ctpd99vQkPvwZXobx0CYYMUWaTldaxIyxerExvF35F4lhdVJN06LR6LdAF2Aao5/nE1ZZCnjsX7r7bO3UTbmGxWJj82Sy+nbeEbjd2ZNCA+1i9diOPPdIPgLp1bJ/z16wRw4zPJjn1+qGhru22j4+7DoDNWw3cdvNNxcfzC39fw8NDAUg+eoJTaaeLf45rSnKy0ruxd69t2b/+BV9+CbLpol+ROFYnVSQdOq0+CPgMGAJ86d3alHC1pZCXLlU+Cr/y9TcL+XbeEh4d2JfRIx4H4PiJf9iXdIgxzz9h95qQkGC07Vp7sprFrm/Vghs7d2DN+l+549ZudOvakZOp6cz9YRkAdWrXoqCggM+nf8dr457zSh296pdflDU2zpyxPh4QAO+/D2PGSC+lH5I4VidVJB3AK8BSo8lwUKfVe7suitRUZSnk336zLfOxpZCF885lXGDGrPm0uyGekcMfKz7epnVLJk76lL733kazprbjdgoKCsjMzHLqe2gCAoiMqOKyOgO88+a/+d/nc5j04RdERUbQtk0cMYWj2jt2uIHvFyzn9lu6ERIcXDwKvmiaXU5OLhqNxv+2BLdYlAGhL7ygrMVRUrVqytisO+7wStWEe0kcq5fXkw6dVn89cBdqeqSya5eyYVtKim3Z+PGQkCAbtvmprdt2kZOby78e7ktAwJXxzGnpynPWsLBQu9elnkr32rNggKioSF59+dnirwsKCri731DiWjQlrkVTPv7fVxh3/2H32htv7e+WOnlVTg48+yzMnGlb1rq10kvZvLnn6yU8QuJYvbyadOi0+kBgGjDcaDLkX+38sjz7zAgiIiJsji/4cX75XkiWQr6mnTmbAUCruCtvSGazmTXrN3NTFx3169lfzt6Tz4LNZjNnz2VQq2YNh+fM+m4RZ85mMPHVUWg0Gsb9+2kyM633BFq8Yi1LV6xn1hfvE1zG3dHKlaupenELK3/fxd/nYqzKyh1fZXBZDJ88Cf36wfbttmX/93/wzTcQFVXBWgpfIHFsy2hM5Pd9h1j19xabMlfG8dV4u6djDLDJaDLs8XI9ZClkAUCrwsFcWVlXAnvO3MWEhYWS8Npoh9e5+llwdraS9OaXHrwMvPvRNJasWMf0Ke/Qvm0rm/LE3fuY9tX3/HvkUDrr2wPY7Ur+bUciADe08aNxSTt3wv33wz//2Ja99hq8+aYylkP4NYlj9fJa0qHT6lsAAwHHi8qXw9QvPiM2NrZiF8tSyKJQp47teO7pR/l8xnfc2LkD5y9cJDAwgJmfv+uxDZu2G3azfNXPwJXpfjd26UBsY2U6Z80a1YmKjCAiwnq2RUFBAUtWrGfmnAW88+a/ubXXjS6pzz333AUpOXR/5AGo4b4xV5WKYYA5c5T9jnJKrZ8QEQGzZytjtMQ1QeLYlk7XAV2XbjweN9Ilr1dRGkvpVTU9QKfVa4ANwKtGk2FrqbKNQE/gZqPJsPFqr6XRaGKB5OTk5Ir9wdq/X+lyLb0yISgzVz7+WFYm9BfHfoTT26HlKND4193u/EWrOHb8H5o0bsCdt/cgKtL2MUWFZR6DlCXQ2G7SUelpH5WO4fx8eOklmDzZtiw2Vhm/0bZtpeooVCIrBQ5OhZhObk2AvcWtcZw8B4KrgP2kw2PTt7zV0zEC2Fs64fC4pUuVOfqXLlkfDw6GqVNlZULhMwb0u0bXijlzBh56SNnvqLSbb4b586FmTc/XS4gKuBbi2FtJx4NAT51WX9Zk4w2F02c3GU2GXi797gUF8J//wOuv25bVqQOLFsGNrunSEkK4yR9/KL2Uhw/blo0cqYzPkl5KIVTFW0nHMeBPB2WNgXDgOJBVeK7ryFLIQvi+xYvh0UeVDRhLCgmBL76Axx/3Tr2EEGXyStJhNBkGOyorMaZjsDNjOsrl8GFl/Q1ZClkI31RQAG+9pcxCKa1ePaWXsksXj1dLCOEcb0+Z9Zyff1bW2DhrvZkOAQHwwQfKqoWyFLIQ6nXxIgwerExfL61TJ6X3o359j1dLCOE8/xrCb4/FAp98Ar172yYc1avDTz/J3gtCqN3ff0PXrvYTjsceU3aBloRDCNXz756Oy5dh+HCYNcu2TJZCFir1199HmP3dIho3rM/xlJM0alCPoY/1J/AqS+8vXbGePXuTqFo1kpOp6TSLbcSwIQOKrzObzcz8ZiFLlq/jXMZ5mjRqwOOPPsgdt3bzxI9VcevXK72U585ZHw8MVAaLjholNw1CdSSO7VNd0uGymSr//KMshbxjh22ZLIUsVOrQ4aMMGzGezydPpHV8CywWCyNfTODDT2YwdszTDq+bM3cxm7fuZPqUd9BoNMXXTZ/1A88MHQTAtJnz2Jd0kAf+rzepp9JZsXoDr7zxAYGBAS5bgMilLBZl7Y0XX1TGcpRUvboyHfa227xSNSHKInHsmH8+Xtm+XZmJYi/heP11ZbCZJBxChT6YPJ34ls1oHd8CAI1Gw+BH7mfB4tX8+ZedqaGFVq7ZQJvWLdEU3vFrNBq639iRjZuVGDh7LoPU1DQ++3giTwzuz/iXnmXKx2+i0Wj4dt4St/9c5Xb5sjLLbMwY24SjTRswGCThEKolceyY/yUdX3+tLF1+8qT18YgIZZrsxImy94JQpX9OnmJX4l507dtYHW/XphWBgYEsXbHe4bXBQUEYTda7T545l0FMTDUA9uw9wPAnH7Eq79D+eho3rMfJ1HTX/ACukpKixPCcObZl998P27bBddd5vl5COEHiuGz+8+6bnw+jR8MTT0BurnVZ06bKH6p+/bxSNeHfLBYLWVnZTv3Lvpzj8HX+2P8XAI0a1rM6HhISTJ3aNTHt2e/w2nvuvJn9Bw7xzgdTycvP50RKKut+2cpzT/8LgJt7dKFe3do210VEVKFxIxUNwNy2Teml3LnTtmziRFi4ECIjPV8v4fckjj1DdWM6KmzwYOUPVmm33go//AA1HG8fLIQ9SQcOsWjZWnYYdvPe22M5feYckz6cSt977+CpJx4uPu9kahp9+j/l1GvWq1ubFQun2y1LSz8DQHS07aO/atFRHDmW4vB1B/bvw6HDR/lx6Rp27z1AnVo1mPrfidSt43ijwvx8M8dPnOTfo1Sy3P/8+cpOsKVvGiIjlTFYfft6pVrCt0kcq4v/JB32Eo7Ro5U1OIL858cUntMqvjmtDh5m/YatZGVlk5Z2mtbxLWx2haxZI4YZn01y6jVDQx0vy51b+GYbHGz7+xoSEkxOTq7N8ZLGjXmaffv/4u/kYxw5eoKNv+7g4QfvdXj+r78ZaNK4Aff07uVU3d1u7FjbY82aKbPM2rSxLRPCCRLH6uKf78YhITBtmjIQTYhKOHDwb65v1YI9e5N4YnB/Huh7p805ISHBaNu1rvT3qhZdFVDuXErLzzdTvVpVh9dmZmXxwtj/MGrEEMLDwpiQ8DEfTFbuxOz9wcrJyeWb75fwbsJLBKh1jNPtt8O8eRAT4+2aCB8ncawevlHL8qhXDzZvloRDuMT2HSZS/jlFv//r7fCcgoICLl685NS/S5lZDl+nZo3qAFy4cNGm7Pz5i9Su5fgR4XsfTaNRw3p07aSlfdtWfPvVRzSNbcjU6d+RnX3Z5vwPJk/nhecet/t8WBXGjIFVqyThEC4hcawe/tXT0bmzMh1WViYULpB89AQpJ08xdHD/4rsXe1JPpbvkWbC2XWuCgoI4fiLV6nhefj6paen06tHZ4etu/HUHI599rPjratFVGfnMY7ww7j8cOXqCVvFXFsGbPusHbrvlJm64Ps6pOntUaKiyB9Jgh9szCVEuEsfq4j9Jx4MPKoPNwsK8XRPhJ37bbiQwMID+/e4u8zxXPQuOioqks74diXv2WR3f+8ef5Obm0fu2HoCyIuHZcxnUqnnljikyMoKMDOs7qwb16wJQvXp08bH5P64ktnFDuujbW527ectOenTr5NTP4Da1a8Py5co+KkK4iMSxuvhP0vH++5JwCJfauj2RDu3bUKtm2V38rnoWDDB82CMMG/EKSQcO0Sq+ORaLhdlzF3HHrd2Ib9kMgHc/msaSFeuYPuUd2rdtBUD/++9i8fJ1PPTgPURFRgCwaetObuqqKx75/tO6zSxb9TO9undhxqz5xd/z6PGU4tf2Kkk4hBtIHKuL/yQdsveCcKHsyzmY9uzjhRGPe/T7toq7jqn/nciM2fOJbdKQ9PQzNG/WhGeGDSo+p2aN6kRFRliNvh/yrweIjIxg3Ovv06hBPTQaDWFhoUya+CIAhsTfeeM/n5Cfn0/Sn39bfc+goCDGPPeEZ37AstT2nefSwjdIHKuPxmKxeLsOlaLRaGKB5OTkZGJjY71cG6Fqx36E09uh5SjQ+N8YarfJPAYpS6DxA1BDX7q00tm+xLBwWlYKHJwKMZ3s/S6KsiTPgeAqEDfSXqnH7trlL68QQgghPEKSDiGEEEJ4hCQd4tpRNO7HUlD2eaKUov8vGTclvK3od1BiuPwKUEMMS9Ihrh0BoYAGzI4X9hF2mLMBDQTK7DDhZYFhys2DOdvbNfEtFguYc1QRw5J0iGtHlYYQEAiZR7xdE99yKVn5f6vS0Ns1Ede6kGoQXFViuLxy0qDgsipiWJIOce2oGgcBYZDxOxTkebs2viH3HGQmQ5XGyh98IbxJEwDRrSH3vJIMi6uzWOBsImiCIPp6b9dGkg5xDQkMg1pdIS8DTiyG7BQlIIWtgny4eAiOLwRNINTu7u0aCaGo0QlCouHkCuUGwmy7J4kolHMGUtfApb8gqgVUaeTtGvn+4mCt49us3X/gD29XQ1RA/wcGALDgx/lXOdOF6t6u9HKc3qa8oQaEQVCk8sYqFJY8yLsAFjMEhkDjByG6lc1p/R8YwOHDyfuMJkOlbp8khn2bx+M4rDY0GwLJsyBtE6RthODowjFbQlGgjHvJuwgBwVA1HmIH2V1E01Vx7CyfTzqEKBeNBurfDdW1cH4fXPob8jOVN1ihCAiBqOuUP1TRreWxilCfKvUhbjRcOADnkyDnNBTkertWKqKBkOpQvb0Sw5FNVbMgoiQd4tqj0Sh/tKrUB273dm2EEBURVAViOij/hM9QR+ojhBBCCL8nSYcQQgghPEKSDiGEEEJ4hM+P6SjaJffEiRNerokor8zMTACOHDni3YqICsnMzOTy5cvBGo0myGKx5Ff0dSSGfZvEsW9zVRw7yx+2tu8G/OrteghxDWtqsViOVPRiiWEhVKFScewsf0g6QgE9cBKQeY9CeN6JytwhSQwLoQqVimNn+XzSIYQQQgjfIANJhRBCCOERknQIIYQQwiMk6RBCCCGER0jSIYQQQgiPkKRDeIROq79Zp9Xf5+16CCEqTuJYVJbPLg6m0+qvA94AbgCygTDgC6PJ8KVXKyas6LT6DsAk4A5gIrCsjHOlTVVCp9UHAs8DQ4A4IA9IBD4wmgwrHVxTrvaT9vYdEse+xxMxXBE+2dOh0+rbo/znaYBORpPhRpT/3I91Wv10b9ZNKHRafTWdVv8yMAjo4sT57ZE2VQWdVq8BfgD+C1wPhAJRQE9ghU6rf97ONe0pR/tJe/sGiWPf5IkYriifSzp0Wn00SpadDzxrNBnyAIwmw1bgA2CYTqsf4r0aikLnjSbD+0aT4UVgdVknSpuqzpMof6h6AeFAJHAPcLiw/AOdVt+g6OTytp+0t0+ROPZNbo3hyvC5pAN4BmgELDSaDBdLlc0s/Pi2TqsP9my1RElGk6HkqnOXr3K6tKm6DAfuMpoMm4wmQ77RZMgymgyrgPtQumhDgbtKnF/e9pP29hESxz7L3TFcYb6YdAwr/LixdIHRZDiOksk1AG7zYJ1E5UibqoROq48D1hpNhiOly4wmwz5gV+GXNUoUlbf9pL39k7SrCngohivMp5IOnVZfC2he+OV+B6f9UfjxDvfXSFSWtKnqHEYZKOjIscKPR6H87Sft7Z+kXVXFrTFc2cr52uyV60t8nuLgnH8KP7Zxc12Ea0ibqkjhs9y8Mk6pC+QA6wq/Lm/7SXv7J2lXlfBADFeKT/V0ADElPi/93KnIhcKPtd1cF+Ea0qY+QqfVhwLtgTlGk+FM4eHytp+0t3+SdvUBLorhSvG1pKNKic9zHZyTU/gxws11Ea4hbeo7+qHcQb1S4lh520/a2z9Ju/oGV8Rwpfha0pFd4nNHo2iLjme5uS7CNaRNfYBOq48A3gIGlrhDgvK3n7S3f5J2VTkXxnCl+FrSkVri80gH5xQdP+XmugjXkDb1DVOA940mw/pSx8vbftLe/knaVf1cFcOV4mtJRxJQNG+8noNzio7vc391hAtIm6qcTqufAPzlYCnk8raftLd/knZVMRfHcKX4VNJhNBnOAr8XftnawWlFI3E3uL9GorKkTdVNp9UPA6KNJsM79srL237S3v5J2lW9XB3Dla2PTyUdheYVfuxeukCn1dcBWgJngbWerJSoFGlTFdJp9QMAvdFkeMlB+b2Fn5a3/aS9/ZO0q8q4MYYrzBeTji+BdOAhnVZfpVTZ4yg/00dGkyHb5krhLeGFHx39vkmbqoxOq78L6As8a6csQqfVv4Yy3x/K337S3r5J4tiHuDmGK0xjsViufpbK6LT63sBilOzsaaPJkKfT6vXAemALcJ/RZDB7s45CodPqa6B03dUHfgF6G02GfDvnSZuqhE6r7w6sAUIcnBIIZAJ1jSbDpcJrytV+0t6+ReLYt3gihivKJ5MOAJ1W3xZ4FWX51iyU+cOzgSnyS+19Oq0+ENgBxGM9tzsd2Go0Ge63c420qZfptPqWgAGoepVTZxpNhqGlri1X+0l7q5/Ese/xZAxXhM8mHUIIIYTwLb44pkMIIYQQPkiSDiGEEEJ4hCQdQgghhPAISTqEEEII4RGSdAghhBDCIyTpEEIIIYRHSNIhhBBCCI+QpEMIIYQQHiFJhxBCCCE8QpIOIYQQQniEJB1CCCGE8AhJOoQQQgjhEZJ0CCGEEMIjJOkQQgghhEdI0iGEEEIIj5CkQwghhBAeIUmHEEIIITxCkg4hhBBCeIQkHUIIIYTwCEk6hBBCCOER/w90J3f/yLZEJgAAAABJRU5ErkJggg=="
     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "Exploratory visualisation is usually quick and dirty, and flexible too. Some exploratory data viz can be automated, and some of the packages we saw in the chapter on {ref}`exploratory-data-analysis` can do this. For an EDA package that's explicitly built with visalisation in mind, check out [SweetViz](https://github.com/fbdesignpro/sweetviz). Beyond you and perhaps your co-authors/collaborators, not many other people should be seeing your exploratory visualisation.\n",
    "\n",
    "The second kind, scientific visualisation, is the prime cut of your exploratory visualisation. It's the kind of plot you might include in a more technical paper, the picture that says a thousand words. I often think of the first image of a black hole {cite}`akiyama2019first` as a prime example of this. You can get away with having a high density of information in a scientific plot and, in short format journals, you may need to. The journal *Physical Review Letters*, which has an 8 page limit, has a classic of this genre in more or less every issue. Ensuring that important values can be accurately read from the plot is especially important in these kinds of charts.\n",
    "\n",
    "The third and final kind is narrative visualisation. This is the one that requires the most thought in the step where you go from the first view to the end product. It's a visualisation that doesn't just show a picture, but gives an insight. These are the kind of visualisations that you might see in the *Financial Times*, *The Economist*, or on the BBC News website. They come with aids that help the viewer focus on the aspects that the creator wanted them to (you can think of these aids or focuses as doing for visualisation what bold font does for text). They're well worth using in your work, especially if you're trying to communicate a particular narrative, and especially if the people you're communicating with don't have deep knowledge of the topic. You might use them in a paper that you hope will have a wide readership, in a blog post summarising your work, or in a report intended for a policymaker."
   ],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "## Narrative Data Visualisation\n",
    "\n",
    "As discussed, the name of the game here is to communicate a particular narrative. Let's see what tricks we can use to help do this.\n",
    "\n",
    "### Drawing Attention to Enhance Narrative Visualisation\n",
    "\n",
    "According to data visualisation master Jon Schwabish's book *Better Data Visusalizations* {cite}`schwabish2021better`, there are 16 ways to draw an audience's attention in a chart:\n",
    "\n",
    "1. Shape\n",
    "2. Enclosure\n",
    "3. Line width\n",
    "4. Saturation\n",
    "5. Colour\n",
    "6. Size\n",
    "7. Markings\n",
    "8. Orientation\n",
    "9. Position\n",
    "10. Sharpness\n",
    "11. Connection\n",
    "12. Length\n",
    "13. 3D\n",
    "14. Curvature\n",
    "15. Density\n",
    "16. Closure\n",
    "\n",
    "![Preattentive Visual Processing, by @jschwabish.](https://github.com/aeturrell/coding-for-economists/raw/main/img/preattentive.jpg) The different ways to trigger preattentive visual processing, by @jschwabish.\n",
    "\n",
    "But be warned: not all of these are equivalent! It's much easier to perceive differences in length than it is differences in, say, volume. So if you want your audience to be able to make comparisons or quantitative assessments, you need to pick what techniques you use from this list carefully. Roughly in order of how easy they are to perceive quantitatively, the features are: one common axis, two axes, length, slope, angle, parts of whole, area, volume, saturation, and hue.\n",
    "\n",
    "**Shape**\n",
    "\n",
    "Shape can draw the eye. One good example of this is a bubble chart, which is a scatter plot (and so has x and y dimensions) that encodes another dimension through the size of the circles used to denote the location in the x-y plane. The most famous examples are probably the gapminder charts as popularised by Prof Hans Rosling.\n",
    "\n",
    "But another good example is the Treemap. The example bleow, different continents are shown in proportion to their population and we very quickly see that Asia contains most of the world's population."
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "source": [
    "# World Bank CO2 emissions (metric tons per capita)\n",
    "# https://data.worldbank.org/indicator/EN.ATM.CO2E.PC\n",
    "# World Bank pop\n",
    "# https://data.worldbank.org/indicator/SP.POP.TOTL\n",
    "# country and region codes at http://api.worldbank.org/v2/country\n",
    "from pandas_datareader import wb\n",
    "df = wb.download(indicator='EN.ATM.CO2E.PC',\n",
    "                  country=['US', 'CHN', 'IND', 'Z4', 'Z7'],\n",
    "                  start=2017, end=2017)\n",
    "df\n",
    " \n",
    "# create dataset\n",
    "df = pd.DataFrame()\n",
    "\n",
    "height = [3, 12, 5, 18, 45]\n",
    "bars = ('A', 'B', 'C', 'D', 'E')\n",
    "\n",
    "# Choose the width of each bar and their positions\n",
    "width = [0.1,0.2,3,1.5,0.3]\n",
    "x_pos = [0,0.3,2,4.5,5.5]\n",
    " \n",
    "# Make the plot\n",
    "plt.bar(x_pos, height, width=width)\n",
    "\n",
    "# Create names on the x-axis\n",
    "plt.xticks(x_pos, bars)\n",
    " \n",
    "# Show graphic\n",
    "plt.show()"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "source": [],
   "outputs": [
    {
     "output_type": "stream",
     "name": "stderr",
     "text": [
      "/Users/aet/opt/anaconda3/envs/codeforecon/lib/python3.8/site-packages/pandas_datareader/wb.py:592: UserWarning: Non-standard ISO country codes: Z4, Z7\n"
     ]
    },
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "                            EN.ATM.CO2E.PC\n",
       "country               year                \n",
       "China                 2017        7.225769\n",
       "East Asia & Pacific   2017        6.237253\n",
       "Europe & Central Asia 2017        6.721800\n",
       "India                 2017        1.719190\n",
       "United States         2017       14.805882"
      ],
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>EN.ATM.CO2E.PC</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>country</th>\n",
       "      <th>year</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>China</th>\n",
       "      <th>2017</th>\n",
       "      <td>7.225769</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>East Asia &amp; Pacific</th>\n",
       "      <th>2017</th>\n",
       "      <td>6.237253</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Europe &amp; Central Asia</th>\n",
       "      <th>2017</th>\n",
       "      <td>6.721800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>India</th>\n",
       "      <th>2017</th>\n",
       "      <td>1.719190</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>United States</th>\n",
       "      <th>2017</th>\n",
       "      <td>14.805882</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ]
     },
     "metadata": {},
     "execution_count": 28
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "source": [],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "### 2. Enclosure\n",
    "\n",
    "An enclosure is something that wraps around something else. We'll do an enclosure around some special bars within a bar chart to demonstrate this, making use of the barley data from the **vega_datasets** package (part of another visualization library)."
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "source": [
    "from vega_datasets import data\n",
    "\n",
    "# Grab data\n",
    "barley = data.barley()\n",
    "barley = pd.DataFrame(barley.groupby([\"variety\"])[\"yield\"].sum())\n",
    "barley = barley.sort_values(by=\"yield\")\n",
    "\n",
    "# Decide on special entries\n",
    "relevant_entries = [\"Peatland\", \"Glabron\", \"No. 462\"]\n",
    "# Find key properties of special entries to enclose: we need the \n",
    "# bottom and the width of rectangle\n",
    "min_pos = min([barley.index.get_loc(x) for x in relevant_entries])\n",
    "max_yield = barley.loc[relevant_entries, \"yield\"].max()\n",
    "\n",
    "# plot standard bar chart\n",
    "fig, ax = plt.subplots()\n",
    "ax.barh(barley[\"yield\"].index, barley[\"yield\"], 0.35, zorder=2, alpha=0.3)\n",
    "# add rectangle to **enclose** special values\n",
    "left, bottom, width, height = (0, min_pos-0.5, max_yield, len(relevant_entries))\n",
    "rect = plt.Rectangle((left, bottom), width, height,\n",
    "                    alpha=0.3, zorder=1, lw=0)\n",
    "ax.add_patch(rect)\n",
    "# Add text to explain enclosure\n",
    "ax.annotate('Entries we want \\nto draw attention to',\n",
    "            xy=(max_yield, min_pos+len(relevant_entries)//2),\n",
    "            xycoords='data',\n",
    "            xytext=(40, 10),\n",
    "            textcoords='offset points',\n",
    "            arrowprops=dict(arrowstyle=\"->\"))\n",
    "# Tidy up plot\n",
    "ax.set_xlim(350, None)\n",
    "ax.set_xlabel(\"Yield\")\n",
    "ax.set_title(\"Title\")\n",
    "plt.show()"
   ],
   "outputs": [
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     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "### 3. Line Width\n",
    "\n",
    "For this one, let's get the productivity per worker of several developed nations.\n",
    "\n",
    "\n",
    "\n"
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "source": [
    "import pandasdmx as pdmx\n",
    "\n",
    "# Get productivity data for select countries since 2010\n",
    "oecd = pdmx.Request('OECD')\n",
    "data = oecd.data(resource_id='PDB_LV', key='GBR+FRA+CAN+ITA+DEU+JPN+USA.T_GDPHRS.CPC/all?startTime=2010').to_pandas()\n",
    "df = pd.DataFrame(data).reset_index()\n",
    "# Renormalise to 2014:\n",
    "loc_vals_2014 = df.loc[df[\"TIME_PERIOD\"]==\"2014\", [\"value\", \"LOCATION\"]]\n",
    "loc_vals_2014 = loc_vals_2014.set_index(\"LOCATION\").to_dict()[\"value\"]\n",
    "df[\"value\"] = df.apply(lambda x: 100*x[\"value\"]/loc_vals_2014[x[\"LOCATION\"]], axis=1)\n",
    "df.head()"
   ],
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "  LOCATION   SUBJECT MEASURE TIME_PERIOD       value\n",
       "0      CAN  T_GDPHRS     CPC        2010   87.763222\n",
       "1      CAN  T_GDPHRS     CPC        2011   90.706798\n",
       "2      CAN  T_GDPHRS     CPC        2012   91.659862\n",
       "3      CAN  T_GDPHRS     CPC        2013   96.081834\n",
       "4      CAN  T_GDPHRS     CPC        2014  100.000000"
      ],
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>LOCATION</th>\n",
       "      <th>SUBJECT</th>\n",
       "      <th>MEASURE</th>\n",
       "      <th>TIME_PERIOD</th>\n",
       "      <th>value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>CAN</td>\n",
       "      <td>T_GDPHRS</td>\n",
       "      <td>CPC</td>\n",
       "      <td>2010</td>\n",
       "      <td>87.763222</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>CAN</td>\n",
       "      <td>T_GDPHRS</td>\n",
       "      <td>CPC</td>\n",
       "      <td>2011</td>\n",
       "      <td>90.706798</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>CAN</td>\n",
       "      <td>T_GDPHRS</td>\n",
       "      <td>CPC</td>\n",
       "      <td>2012</td>\n",
       "      <td>91.659862</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>CAN</td>\n",
       "      <td>T_GDPHRS</td>\n",
       "      <td>CPC</td>\n",
       "      <td>2013</td>\n",
       "      <td>96.081834</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>CAN</td>\n",
       "      <td>T_GDPHRS</td>\n",
       "      <td>CPC</td>\n",
       "      <td>2014</td>\n",
       "      <td>100.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ]
     },
     "metadata": {},
     "execution_count": 4
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "Now let's plot all of the countries but highlight just one, for Japan, to be different via its line width."
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "source": [
    "fig, ax = plt.subplots()\n",
    "for i, country in enumerate(df[\"LOCATION\"].unique()):\n",
    "    df_sub = df[df[\"LOCATION\"] == country]\n",
    "    if(country!=\"JPN\"):\n",
    "        linewidth = 0.8\n",
    "        zorder=1\n",
    "    else:\n",
    "        linewidth = 5\n",
    "        zorder=2\n",
    "    ax.plot(df_sub[\"TIME_PERIOD\"], df_sub[\"value\"], label=country, lw=linewidth,\n",
    "            zorder=zorder)\n",
    "ax.set_title(\"Output per hour worked (2014 = 100)\", loc=\"right\")\n",
    "ax.yaxis.tick_right()\n",
    "fig.autofmt_xdate()\n",
    "ax.spines[\"right\"].set_visible(True)\n",
    "ax.spines[\"left\"].set_visible(False)\n",
    "ax.legend(frameon=False)\n",
    "plt.show()"
   ],
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "text/plain": [
       "<Figure size 900x600 with 1 Axes>"
      ],
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"
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    "## 4. Saturation\n",
    "\n",
    "Saturation is a parameter that controls how intense colours appear. High saturation colours are more vivid. The easiest way to influence saturation in **matplotlib** is to the change the parameter `alpha`, which actually controls transparency. Setting it to zero means that you won't be able to see the feature it relates to at all. You should also note that some types of graphics do not support transparency, for example .eps files: encapsulated postscript, sometimes required by journals for figures."
   ],
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  }
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